Emissions Policy Renewables

The capacity factor of wind

Guest Post by John Morgan. John is Chief Scientist at a Sydney startup developing smart grid and grid scale energy storage technologies.  You can follow John on twitter at @JohnDPMorgan.

A lot of ink is spilled on wind intermittency, and not necessarily based in data.  So I have extracted and analyzed a high resolution dataset of a year’s worth of Australian wind power for a number of interesting properties.  I previously wrote about the capacity factor as a limit to the share of electricity that wind and solar can acquire, so I also ask how wind capacity factor changes with time, place and season.  In particular, how does it change during sunlight hours and what does it mean for the capacity factor limit on renewable energy penetration?

Australian wind fleet data

The Australian Energy Market Operator (AEMO) publishes data on all generators connected to the National Electricity Market (NEM) grid, which covers the eastern states including Tasmania, but excludes Western Australia and the Northern Territory.  The data includes power generation every five minutes for every generator for the last year, their capacities as registered with the grid operator, and more.  It is not very accessible, being in the form of thousands of SCADA data files, many of which contain errors.  But with a bit of work the data can be extracted.  Here, for instance, is the output of all grid-connected wind farms at five minute resolution over one year:

Wind capacity factor

Here is the top level summary of the Australian wind farm fleet over the last year:

The nameplate capacity is the total capacity of all wind farms – 3753 MW.  But the whole fleet only manages 3238 MW at peak.The whole is less than the sum of its parts – half a gigawatt less in this case. Why is this?

The fleet is comprised of wind farms distributed over a large area of eastern Australia.  To achieve maximum theoretical power the wind would have to be blowing at the optimum speed for each wind farm, at all wind farms, simultaneously.  This is a statistical improbability and quite possibly a hydrodynamic impossibility, as it would require a high velocity correlated flow field over very large distances.

So while we often hear that the wind is always blowing somewhere, it is equally true that it is always not blowing somewhere else, and the fleet output never achieves full capacity.  Australia in theory has 3753 MW of wind capacity, but this will never be realized in practice.  Similarly, statements like: “The US added x GW of wind capacity last year”, overstate the capacity addition because the new wind build is unlikely to ever produce its maximum power in full correlation with the rest of the fleet.

In other words, national capacity statistics overstate the potential output of wind.  The flip side of this is that the capacity factor limit underestimates the potential for wind penetration.  We can push the penetration of wind a bit higher than the capacity factor – generation would start to exceed demand at 33% share, rather than 29% share.

Wind correlation times and the synoptic scale

Over what distances are wind farm outputs correlated?  Its actually easier to ask, over what period in time is wind power correlated?  This information is contained in the wind power autocorrelation function, which we can calculate from the dataset:

The autocorrelation function tells us how long the influence of a particular state of wind persists.  If its windy now, for how long will it remain windy?  Surely for the next five minutes.  But will it still be windy tomorrow?  The autocorrelation function is a “memory” function that tells us how long wind “remembers” how hard it was blowing.

The autocorrelation function decays in about 40 hours (since we have 5 minute data the x-axis is in units of 5 minute “lag”s).  This means wind, on average, bears no relation to its output 40 or more hours ago.  Wind has a “correlation time” of about 40 hours.

Its interesting to interpret this as the time for a body of moving air to pass over a windfarm.  If we knew how fast it was moving we’d know how big it was.  Wind resource maps suggest a velocity of about 7-8 ms-1, so that interpretation suggests a wind correlation distance of about 1200 km – the “synoptic scale”.  This seems a pretty reasonable estimate of the size of weather systems and can in fact be done for a single wind farm with a similar result.  Its remarkable to be able to pull large scale geographic information out of just the power fluctuations of a single wind farm!

If we wanted to cover intermittency we would need to ensure our wind fleet is dispersed over distances of 1200 km and more, so that the output of at least some of its wind farms will be uncorrelated.  This smooths the output of the wind fleet, reducing maximum output below the nameplate capacity, but increasing the amount of energy that can be integrated without having to spill, store or manage excess generation.

Wind power ramp rates

Wind output is constantly changing and requires the rest of the grid to be flexible enough to ramp up power or shed load to balance wind fluctuation.  This rate of change is just the time derivative of wind power.  The plot below shows this “acceleration rate” throughout the year.  It’s a normal distribution, the symmetry showing that wind power picks up as fast as it drops off, and that the grid needs to be responsive at a rate of 20 MW per minute, in both directions, to cover most conditions.

As more wind is added, the flexibility of the rest of the grid will have to increase proportionately – double the wind energy would require about 40 MW/min ramp rate.  But this additional ramping ability must be delivered by the shrinking dispatcheable generator sector.  So the intrinsic flexibility of the rest of the grid must increase, and faster than in simple proportion to wind penetration.  Practically that means increasingly strong pressure to shift from coal generation to gas as wind share grows.

Low wind days

Lets look at the distribution of low wind days.  We can ask, for how many days was wind output below some level?  For instance, we can find 29 days in which output was below 10% of capacity, and 127 days below 20% capacity.  127 days is, incidentally, pretty close to the number of weekends and annual leave of most Australians – Australian wind is obviously governed by Australian workplace awards!

The plot below shows the number of days below a particular output level.  Interestingly, the daily average power output never exceeded 75% of capacity, or 2810 MW, almost 1 gigawatt less than installed.  The fleet was never totally becalmed, but the lowest recorded day in the year saw output of just 2.7%.

Also of interest is the number of consecutive low wind days.  This affects the strategies we might use to cover wind outages – whether we store energy in batteries, or with pumped hydroelectricity, or shed load, cut in gas generators, or coal.  For instance, of the 29 days of wind output below 10% of capacity, 15 are single isolated low wind days, and then there are 7 pairs of 2 day long low wind runs.  If we look for sequences of days with less than 20% output, we find 2 runs of 5 low wind days.  The full distribution is shown below.

The number and distribution of low wind days show that while wind contributes energy, it does not provide capacity.  Alternative generation capacity must be available to meet the near absence of wind about one day in ten, and for two or more days in sequence.  But many of these low wind events are of just a single day duration.  This is a difficult timescale for coal plants, so again, increasing wind penetration drives the residual mix towards gas.

Wind capacity factor by month and day

To get a handle on wind seasonality we can look at monthly output and capacity factors.  Each point in the plot below is the average power output for a day in the year.  The coloured blobs show the distribution of power output in each month.  Also shown is the capacity factor for each month.

The nameplate capacity factor varies from month to month (30%±5% covers it). Every month has low wind days and high wind days and everything in between with little seasonal structure.  The winter months have more high wind days, but they also have more low wind days, and one cannot confidently assert the monthly CF variation is greater than noise, in this year.

We can see this in a box plot of daily capacity factor – the data distribution is very wide and a capacity factor of 25% is consistent with the data for every month.  The highest daily capacity factor for the whole fleet was 75%, and the lowest was 2.7%.  These maximum and minimum output days both occurred in winter, when solar power is at a minimum.

Wind capacity factor by hour

We can push this through to a still finer grain by looking at wind output by hour of the day.  The following plot shows the average capacity factor by hour of the day, for each month.  We can see if wind picks up or drops off in any consistent way through the course of a day.  The summer months show some daily pattern, perhaps, but the rest of the year does not:

Does the wind output drop when the sun is shining?  It would be convenient if it did, as it would allow more solar  power on the grid.  Lets nominate solar hours as 10 am – 4 pm, and compare solar hours with non-solar hours.

There is no difference between wind capacity factor when the sun is high in the sky and when it is not.  Wind does not cooperate with solar by subsiding in the middle of the day.  Possibly wind blows harder when clouds block sunlight.  Unfortunately I don’t have a dataset for solar PV output and can’t test this.  My guess is that the number of days and the number of sites at which such anticorrelation occurs is not large enough to shift the average output of the total fleet enough to change the overall picture.

What does this mean for the capacity factor threshold?

As explained in detail by Jenkins and Trembath, it is increasingly difficult to build more wind or solar capacity as their market share approaches their capacity factor (CF) because they will then, at times, be producing energy in excess of demand.  The economic drag incurred by dealing with surplus generation by storage, curtailment or demand reduction undermines the economics of building additional capacity.  The capacity of wind and solar is thus limited to be roughly numerically equal to 100% of grid demand.

In “Less than the sum of its parts” I argued that adding solar to the mix actually reduces the combined amount of wind and solar energy that can be added to the grid.  This is because solar competes with wind for share of capacity, but contributes less actual energy due to its lower capacity factor.  Building solar thus reduces the maximum amount of renewable energy we can get onto the grid.

You can get around this if wind and solar generate at different times of the day, or year.  But from the data above we can say that wind does not drop during the day or pick up at night, to any significant degree.  The capacity factor of wind during “solar” hours is the same as during “non-solar” hours.

Turning to the seasonal variation, its possible wind has a higher capacity factor in winter when solar output is low, but the evidence of the last year is not compelling.  The lowest wind capacity factor in the year was actually in the winter month of June, and January in high summer was one of the higher producing wind months.  The winter months have more high wind days, but they also have more low wind days.

If there is some seasonal synergy between wind and solar, its not particularly strong, and the contention that the maximum share of renewable energy is achieved by building wind and not solar seems sound.

But the capacity factor threshold does require an adjustment.  Recall the peak wind output was only 3238 MW, less than the nameplate capacity of 3753 MW.  So we could build more capacity without fear of excess generation.  Instead of spillage or storage being required at 29% wind share, we can accommodate a more generous 33% share.  This greater share of wind energy is possible due to the geographic distribution of wind smoothing out some of the peaks.


There’s a lot of information in noise.  Deducing the size of large scale weather systems from the power fluctuations is pretty cool, as is seeing the signature of spatial distribution of wind farms in a one-dimensional time series.  Notably, a national wind fleet will not achieve full output due to geographical smoothing, but this smoothing also increases the capacity factor threshold for wind share a bit, from about 29% to 33%.

As expected, intermittency means wind contributes energy but not capacity to the grid, meaning wind acts as a fuel saver for fossil plants, which must increasingly shift to gas rather than coal as wind penetration grows, to accommodate higher ramp rates.

The capacity factor does not show strong consistent variation across hours, days or months, and share of renewable energy is limited as Jenkins and Trembath describe.  There is little evidence of a synergy between wind and solar in the Australian grid, supporting my earlier conclusion that a combination of wind and solar can displace less fossil energy than wind alone.  If we really wanted to push towards maximum renewable energy, we would build wind and not solar, and variable renewables share could grow to about 33%.


The Australian Energy Market Operator Generation and Load data can be found at this page.

Five minute data for all generators can be extracted by parsing the SCADA data files in this directory.  Data goes back a little over a year.  Older data is not available – AEMO appear to delete the oldest files on this page on a daily basis.

AEMO lists all generators connected to the grid, by technology here, in the spreadsheet “Registration and Exemption List”, in the tab “generators and Scheduled Loads”.  Each generator has a unique identifier, the DUID, allowing it to be located in the SCADA files.

The SCADA files contain a number of errors – in many files the output of many generators is double counted.  A corrected data set was created by filtering out duplicate generator entries.

The data was extracted and analysed with python code using the excellent SciPy scientific python tools, iPython notebook, pandas data analysis library, with MatPlotLib and Seaborn data visualization libraries for plotting.


By Barry Brook

Barry Brook is an ARC Laureate Fellow and Chair of Environmental Sustainability at the University of Tasmania. He researches global change, ecology and energy.

363 replies on “The capacity factor of wind”

Hi John,

Excellent post, as usual. Thank you. There’s much to discuss. Here’s a few initial comments.

If you haven’t already seen it, I expect you would be interested in Joe Whealey’s excellent analysis of the CO2 Emissions Savings from Wind Power in the NEM in 2014

Second, your capacity figure of 29% for the period Oct 2014 to Sep 2015 is identical to the figure Wheatley got for the NEM for calendar year 2014.

Third, some comments on this paragraph:

If we wanted to cover intermittency we would need to ensure our wind fleet is dispersed over distances of 1200 km and more, so that the output of at least some of its wind farms will be uncorrelated. This smooths the output of the wind fleet, reducing maximum output below the nameplate capacity, but increasing the amount of energy that can be integrated without having to spill, store or manage excess generation.

Wind farms in the NEM are dispersed over a triangular area of about 1200 km east-west by 800 km north-south. And sometimes there is no electricity generate by any wind farms. For example, in May 2010, there were 75 5-minute periods when wind farms generated zero power; some of this time they were drawing more power than they generated, up to a maximum of 4 MW (from memory).

The amount of wind that has to be spilled is effected mainly by local grid constraints rather than the total wind generation in the whole grid.

Fourth, I’d also mention an excellent series of posts on Energy Matters for readers who may not have seen them. A summary of the 24 posts is here with links to each of the 24 previous posts. The last few are particularly interesting.

Fifth, regarding:

This is a difficult timescale for coal plants, so again, increasing wind penetration drives the residual mix towards gas.

True. And greatly increase the wholesale cost of that electricity.


… we would build wind and not solar, and variable renewables share could grow to about 33%.

If wind’s share of generation increased to 33% (I realise you are talking about wind+ solar share), the CO2 emissions abatement effectiveness of wind generation would decrease to well below 50%. At 20% wind energy penetration, the CO2 abatement effectiveness would be about 60%; that means the CO2 abatement cost would be about 67% higher than is generally claimed. Therefore, at 33% wind share of electricity generation, CO2 abatement effectiveness may be around 40% and the CO2 abatement cost about 2.5 times higher than generally calculated. See the chart in: “What’s the cost of CO2 abatement with wind turbines”:


Peter Lang

If you cared to read the article then you would not claim the low CO2 abatement figures for wind power that you claim.

I have discussed this with you before and you yourself supplied a graph that clearly showed that your claims were unfounded.

Instead of just second guessing what you feel or think it would be much more productive to just post your beliefs that you base your strange CO2 abatement factors upon. And moreover present them in some kind of calculation.

John Morgan clearly states that to integrate wind you need peak power plants based upon natural gas. As natural gas emits roughly 50% less CO2 than a coal fired power plant then the logical assumption is that if the utilities decides to introduce peak power plants and take coal power offline then you have 100% abatement effect for the added wind power times the capacity factor and 50% for the added peak power natural gas power plants times their capacity factor provided the wind power does not go to waste at times with near 100% capacity factor.

Now you claim that John Morgan has got it wrong when he assumes that wind power can go slightly over the realized average capacity factor in Australia at 29% and supply 33% of the electricity without substantially overshooting production.

Both solar and wind is rapidly improving capacity factors and will be doing so in the next decades as a simple consequence of technological improvements. Wind turbines grow and reach higher altitudes with stronger and steadier wind and solar installations are rapidly moving from predominantly roof integrated to utility scale solutions and in utility scale solutions tracking, cleaning, maintenance, inverter/module ratio optimization is common, which increase the capacity factor.

If you over provision with electricity from a variety of low carbon sources then you can much easier make sure that you at all times can meet the electricity demand but you will also end up with un utilized electricity that is in excess and therefore cheap. John Morgan wrote an excellent piece about Synfuels. If we do not start producing Synfuels we will never be able to stop the ongoing climate catastrophe. Electrons are electrons and the final Synfuel will be of equal quality irrespective of its origins. What matters is that the origins are cheap enough and does not entail pollution including excessive GHG emissions.
As per BNC Comments Policy, please supply refs to back up your contentions. Thank you


Has anyone done an analyis of the correlation or lack thereof, between solar and power demand?

Far from the equator there is little solar available in winter while demand is quite high, so solar is rather useless there. However, I would expect that many regions at lower latitudes would ,minimal seasonal variation & have the daytime peak in demand roughly match the peak output from solar power. So there would be some optimal mix of solar & something steady like nuclear to minimize the need for storage & overbuilding of the power supply. If this is so, then to move away from fossil fuel use many regions should build nuclear & solar and avoid installing wind.

But maybe even the most consistently sunny areas have too many cloudy or dusty days, or the peak demand is in the late afternoon & evening, so solar would be less useful than I think.

So can anyone provide a link to such an analysis?


Hi Jim Baerg

It is not for all nations to handle nuclear and nuclear is at present too expensive compared to wind and solar and the gap is widening fast. As an example the solar capacity doubled in just one year in USA last year and the cost of solar is expected to halve within the next five years.

The widening gap problem can change but will probably require a departure from the classic LWR concept.

Some nations such as Bahrain, India, Turkey and more with high insolation are however also building nuclear capacity but in general nuclear is not befitting unless the country has a skilled work force and the strong academic tradition required to handle complex nuclear technology.

Any child can handle PV and not very adept organizations can handle wind turbines.

Nuclear is also a very time consuming technology where the time from the investment is considered to the power plant begins operation can be very long. Most new power capacity in equatorial countries are needed asap and solar and wind is very fast to get up and running.

Another consideration is the lack of sufficient water supply, which put a cap on nuclear unless there is abundant water resources and preferably seawater. Solar and wind are not dependent on water supply as they are not thermal power plants that require cooling water.

As for the updated scenario analysis you ask for links to I think you can expect it to be very difficult to find because the cost of wind and solar is dropping so fast along with the cost of storage that 2-3 years old studies are already inaccurate. EIA is famous for getting it wrong again and again

Anyway for a complete shift away from fossils you need much lower electricity prices because Synfuels that are price competitive with oil products based upon crude oil require a huge expansion in cheap carbon light energy forms.

Developers of new nuclear technology should aim for sub US cent per kWh without subsidies because that is where the price point begins to make it feasible to keep fossils underground.


You say ‘If we really wanted to push toward maximum renewable energy we would build wind and not solar, and varible renewable’s share would grow to about 33%’. A good thing you put in ‘variable’. In fact if we wanted to push toward maximum renewable energy (of both variable and dispatcheable) we’d have solar hot water on all households, waste to energy plants for every 300-500,000 tonnes of non-recyclable waste production in regions and city fringes, and biomass to energy plants of every type (including biogas, advanced biofuels, small to mid-scale CHP).
This could allow us to move (by 2030) up past 50% overall renewable share of energy on a final energy basis, and around 30% of electricity share, with a significant retirement of coal-fired plant.
In this scenario we’d freeze wind capacity expansion about where it is (because further expansion only necessitates ever greater installed capacity fo gas-fired plants) and maximise solar PV. And (quietly forgetting about the very high cost per MW-e actually produced from solar PV) we’d be getting the renewable electricity cheaper than from the mix of wind and the necessary added shoulder and peaking gas-fired plants.
To use my usual reference of Sweden, there they are past 50% final energy from renewables (with over 35% from biomass), and less than 2% of the country’s final energy is from wind (and it is not that they don’t have good wind resources).

I’d be keen for you to do a follow up on your current post that analyses the actual GHG emissions reduction/MW-e produced that added capacity of wind results in (i.e., at present installed capacity, at say 8000 MW installed, and at 17,000 MW installed), and also the real capital cost per MW-e produced by wind at these same installed capacity totals when all added balancing gas generation and associated gas pipeline and grid infrastructure requirements are taken into account.
just as an example, I am aware of a local wind farm in planning in Victoria where the developers say the total capital cost for the erected turbines plus all ancillary works of substations, supply line, roading, trenching, etc., will be $650 million for a 300 MW capacity and 1000 GWh/yr output. Many other wind farms will have comparable total capital costs without adding the external costs. Yet wind power is being marketed to us as ‘the cheapest source of renewable electricity’. I suggest that this whole aspect is not getting enough attention.
As per BNC Comments Policy, please supply refs to back up your contentions. Thank you.


1. Assuming we do use biomass as you recommend why can’t that be used as backup to wind and solar rather than gas.


Peter Farley,

The answer is because the cost of electricity would be prohibitive if we attempted to use biomass to back up for wind power when wind is a large proportion of electricity generation. the back up generators need very high availability – e.g. around 98% like gas – but would have low capacity factor. The cost of logistics and of storing biomass fuel at the power stations to enable them to operate with such high availability would be prohibitive.

This is explained here:

In my response and questions to Mark Diesendorf here:

And the cost of 100% renewable electricity in the NEM using biofuel as back up is compared with the cost of mostly nuclear here: (see Figure 6 for cost comparison, Figure 5 and 7 for CO2 emissions avoided and estimate of the transmission capital cost and cost of electricity.


to Peter Farley, ‘biomass’ actually covers everything from sewage to landfill gas to urban wood wastes and the organic fraction of solid municipal wastes as well as agricultural resiues, organic food processing residues (including abbotoir wastes) and woody biomass from all sorts of forestry and plantation activities. Elsewhere the dry end of these feedstock materials are fuelling either heat plants or combined heat and power plants and these have little ability to ramp up and down fast and obviously the economics of sitting at a production of 30-40% of rated capacity are lousy. These are the bioenergy forms that can be replacing coal plants of various sorts.
Some forms of biomass do have capacity to provide a fast ramp up/down and these are basically the various biogas sources – landfill gas, sewage, and other putrescible wastes. All you need in this case is the adequate capacity of pressurised gas storage tanks. Starting up a gas engine and getting up to full output only takes seconds. Australia might at present have 120-150 MW installed capacity (output of 700 GWh in 2011 and it be maybe 1000 GWh now).
With some stimulus and technical support this could be lifted towards 2-3000 MW within 15 years. There are many wastes that can be used for production of biogas. Grass silage (including unpalatable grasses and weeds), straw pellets, food residues, abbotoir wastes and chicken manure/litter are the most available. Best economics are when there is also a sale and commercial use for the heat.
It is possible to produce methane from woody biomass, or pyrolysis oil from any ligno-cellulosic material, or synthesis gas from dry municipal wastes, and so the availability of gas fuels or liquid fuels produced from sustainably and economically available biomass (and not remote and dispersed forestry harvest residues) can be increased using what is already available.

All of this is now mature technology in commercial use in developed countries, and what the utilisation of biomass is depends on the economics – and within this some of these options do require aggregation of very large volumes of quite low density and low value feedstocks, and usually the capital cost of this large volume plant is high (but rarely higher than that of one single large wind farm).
As per BNC Comments Policy, please supply refs to support your assertions. Thank you.


Thanks for this research John. In my book, The Power Makers’ Challenge, I have an appendix on wind power which covered some of the material you have presented here.

My research showed that in some locations the mean wind speed was just under 7 m/s (25 km/hr) and occurs 10% of the time. Not all sites would have such a high mean wind speed but 7 m/s is thought to be the required profile for a ‘good’ site. Some would argue this is the minimum for commercially viable wind power.

Looking at your image for Australia above there seems to be very few locations with mean wind speeds of 7 m/s on much of the east coast and practically none in Queensland and Northern Territory.

Where does this leave Diesendorf’s research showing the viability of 100% RE?


Whether Nuclear ,Water,Wind or Whatever Humans must start living and Governing to the fact that we only have one Earth and we have to live in balance with what is. Not some new Technology which allows for Human over abuse to carry on a bit longer! CHF


Thank you for this great article John Morgan. Also thanks Peter Long.

How can we get our message to COP21? The Third World has hijacked the United Nations climate talks [COP] to push their own agenda unrelated to Global Warming [GW]. They want to tax the US.

Click to access l05.pdf

Authority comes out of a gun. The Third World does not have the authority to tax the US. Forget about hijacking the climate talks and concentrate on fighting GW. “Developing” countries have to shoulder just as much of the burden as the US.

If The Third World does not share the burden equally and reduce ‘s CO2 output, it is The Third World that will die first. The answer is NO but Hell NO! The US will not fight GW alone. The Third World must use Third World money to shut down coal fired power plants and replace them with nuclear power plants. Do not expect the US to pay for what they must do.

The way to prevent The Third World from making CO2 is to leave them in the stone age.

ANS Nuclear Cafe & COP6

Global Warming and the EPA plan to mitigate:
CONFERENCE OF THE PARTIES Sixth session, part two Bonn, 16-27 July 2001 Agenda items 4 and 7
page 8:
2. Article 6 project activities
The Conference of the Parties agrees:
1. To affirm that it is the host Party’s prerogative to confirm whether an Article 6 project activity assists it in achieving sustainable development.
2. To recognize that Parties included in Annex I are to refrain from using emission reduction units generated from nuclear facilities to meet their commitments under Article 3.1.

Click to access l05.pdf

FCCC/CP/2001/L.5 English Page 13
Issue: Nuclear
Description: Can emission reduction units and certified emission reductions be generated by nuclear power projects?
Options Option A No mention of the possibility of using nuclear facilities for generating ERUs and CERs.
Option B
FCCC/CP/2001/2/Add.2, page3 – Recognizing that Parties included in Annex I are to refrain from using nuclear facilities for generating emission reduction units and certified emission reductions.
There must be more documentation on this. COP6 was in Germany, where the “Green” party has an outsized influence because it is necessary to be allied with the Greens to form a coalition government. The tail wags the dog.
There is a lot more nonsense in those same documents, like the third world taxing the first world, which is not going to happen. Unfccc is not serious about GW at COP6. Will COP21 be any different? Let’s hope so. In the mean time, we need to straighten out the politicians.


I am presently doing some work in Sudan. if you look at the GHG emissions of Sudan you’ll see on some sites a per-capita figure of 0.3 tonnes. I’d be suggesting that it is closer to 1 tonne. India is put as 1.7, Indonesia is 2.6. Most countries in Africa and Asia have per-capita GHG emission levels of below 3 tonnes. The idea is that they are helped to stay below this level, as the real offenders like the USA, Canada, Australia, etc., also bring their levels down.

Yet Sudan and these other countries are heading off to COP 21 with each delegation carryiing a list of the ways they are intending to reduce GHG emissions. The reality is that these counties already with very low per-capita emissions don’t need to look at reductions (though certainly at changing to higher efficiency systems particularly for biomass use).
The critical point is that they have many ways of sequestering major amounts of atmospheric carbon and that they can be assisted to do this. Sudan is only one of the many sub-saharan countries that have the capacity and the land available to replant tens of millions of hectares to forest including wide-spaced agroforestry plantings. And that this can be done with only beneficial results including for food production. The actual cost per tonne of CO2 sequestered would be minimal. Sure they should do it anyway, but a well designed system would be just acting as a catalyst to national efforts towards this end, not a substitute for national effort.
Please note that BNC Comments Policy requires that commenters provide quality and preferably peer review references to support their contentions. This applies on all but the Open Thread where rules are somewhat relaxed.


John Morgan: Recommended reading: Read this on first to see why we need a week’s worth of storage.: “A Nation-Sized Battery”
by physics professor Tom Murphy
Pump Up the Storage”
To store a week’s worth of energy as pumped hydro, for the US, we would have to lift Lake Erie half a kilometer skyward per Tom Murphy.

Book: “Green Illusions” by Ozzie Zehner: A complete renewable energy system for the US would cost 1.4 QUADRILLION dollars.

My estimate for the cost of a battery for the US is $0.5 QUADrillion. 5 times 10 to the eleventh power. About 29 times GDP. How I got it: Fairbanks has a battery that can last 7 to 15 minutes. They paid $35 Million for it. Fairbanks has 30,000 people. That is $1167 per person. Multiply by 400 million people. Divide 7 minutes into a week. Multiply that by the number you got before. You get half a quadrillion dollars. Batteries are out. I did not account for price going up as resources are depleted.

See: Fairbanks Daily News-Miner – “GVEA s Fairbanks battery bank keeps lights on”

To go with renewables only, you need a whole week’s worth of battery power for the whole world because Europe can have a long cold cloudy calm winter. The batteries can run down over several months.

My list of references is too long to put here.

John Morgan: Since batteries rely on chemistry, they aren’t going to improve by the required factor of a million any time soon.


Jim, this piece goes somewhat to your query on solar vs demand, with reference to summer in South Australia, which is when the greatest electricity demand is experienced:

The effect of household PV penetration (which is expressed as a drop in demand, visible on the graphs therein) has been to shift the demand peak from 3-4 pm to 5-6 pm. Fortuitously, this appears to coincide with peak wind production in the hotter months (Nov-Mar) as seen in the hourly analysis above (sea breezes?). Maybe this will enable eking out a few more percent of PV penetration.


Please note that BNC Comments Policy requires that commenters provide quality and preferably peer review references to support their contentions. This applies on all but the Open Thread where rules are somewhat relaxed.


Hi John, in my book “The Power Makers’ Challenge”, I have an appendix on wind variability which covers some of the work you have done here. In that appendix I had a typical mean wind speed of just under 7 m/s (25 km/hr) occurring 10% of the time. Not all sites have such a high mean wind speed but 7 m/s is thought to be the required profile for a ‘good’ site. Some would argue this is the minimum for commercially viable wind power.

Looking at your map of Australia, much of the total country, particularly eastern and central locations do not have mean wind speeds that would be attractive to wind farm builders. Given that much of the population lives near the eastern coast, there must be some serious restrictions to how much wind power can deliver electricity demand to populations in Sydney and Queensland for example.

This must put into question the practicality of 100% renewable energy if one of the major RE technologies, i.e. wind, is not available locally for perhaps more than half the population that currently rely on coal.



That is a fascinating post, however all sources of power generation have a capacity factor of less than 90%. As you point out availability is also a key variable

For example coal in Australia is around 58% capacity factor but about 90%+ availability. According to the latest French data their nuclear is running at 67% CF YTD, again probably 95+% availability. Hydro in Australia is well over 95% availability but averages around 15% CF but is lower this year. Gas is 95% + availability significantly less than 30% utilisation. Even Nuclear in the US which averages about 90% CF varies from 95%+ to around 70% or less availability on a seasonal basis.

Therefore you need significant excess capacity in any known grid scenario. In almost all grids the optimum mix has some sort of storage to minimise over-investment in slow ramping generators and the running costs of spinning reserves. They also have considerable fast ramping capacity

The tricky question is how we integrate them and what is the lowest cost reserve capacity.

I have seen graphs that show that in Europe solar and wind are largely complimentary and others that show they are not, although I think some of the differences between the two are due to the resolution of the time scale and the use of more or less grid integration between countries.

To determine the amount of storage and the optimum capacity factor one needs to understand the demand as well as supply and even the location of the generators. For example west facing solar farms on the western edge of the grid are much more useful for reducing peak demand on hot days than solar roofs in SE Qld. A combined cycle gas plant in North Qld. is of limited help with peak demand in SA or Tasmania.

Also with regard to time. Obviously solar is not available at night but demand is lower so it is much easier to meet demand from hydro, wind and biomass

I am not suggesting that either of the following is the best scenario but in the Australian NEM context here are two (of many) do-able, reliable 98% non carbon electricity options

We could install 50-60 GW of nuclear and keep the hydro, but the optimum nuclear scenario is probably about 35-40GW of nuclear + hydro + 20-30GW of of storage + 8-10GW of gas/biomass to cover extended nuclear outages/non optimal renewable weather.

Or we can build 40-50GW of wind, with the same conventional hydro, 10GW of biomass and 40GW of fixed solar + 10GW of tracking with the existing 10GW gas together with 25GW of storage.

In both cases we could operate quite safely with gas contributing <3% of annual demand and therefore negligible GHG and eliminate 99% of other pollutants.

In both cases if thermal storage and load shifting was encouraged the electrical storage can be reduced to about 15-20GW


Peter Farley,

We could install 50-60 GW of nuclear and keep the hydro, but the optimum nuclear scenario is probably about 35-40GW of nuclear + hydro + 20-30GW of of storage + 8-10GW of gas/biomass to cover extended nuclear outages/non optimal renewable weather.

Or we can build 40-50GW of wind, with the same conventional hydro, 10GW of biomass and 40GW of fixed solar + 10GW of tracking with the existing 10GW gas together with 25GW of storage.

When you consider the economics, the renewable scenario you suggest is out of the question. There is much on this on previous threads on BNC and elsewhere. A very god recent series of threads for EU and EU countries is summarised in a final post on Energy Matters here: “Renewables Future – A Summary of Findings . AEMO also investigated the option of 100% renewables and reported in 2012 or 2013 from memory. They said it was technically feasible but costly, and buried in the text were many caveats such as the cost would be higher than stated in the report.

I do not agree with the capacities you suggest for the largely nuclear option. I’d suggest the least cost option to provide electricity with about the same emissions intensity as France’s electricity (i.e. less than 10% of Australia’s) is about 20 GW nuclear running at about 90% capacity factor (i.e. 18 GE average output with scheduled shut downs timed for periods of lower than average baseload), plus about 20 GW of gas plus about the current capacity of wind and solar. Peak demand in the NEM is about 32-35 GW (varies from year to year) so these capacities would give around 20% capacity reserve. The gas and hydro would run at low capacity factor so emissions from gas would be low. If more hydro or pumped hydro is economically viable then it should and would be developed, but it is not even close to being viable at the moment.


Re the asertion that ‘all power generation plants have a capacity factor of under 90%’, the CF of waste to energy plants is generally above 95% and similarly for landfill gas and sewage gas-fuelled generator systems, and so is level with their availability.
In general WTE plants in Europe operate on some form of arrangement where the power produced has to be accepted, as they operate 24/7 for all but 1-2 weeks of the year.

Similarly the anaerobic digesters taking in city sewage and other main industry putrescible waste streams, and their CF may be somewhat higher than for WTE plants. Biogas fuelled generators drawing from larger landfills and sewage anaerobic digestion systems or AD systems at round-the-clock food processing plants fit into this category. Similarly in Europe many larger biogas-fuelled generating plants with only the minimal gas storage within the reactor and may run at up to 98% CF.

Click to access Biogas_Opportunities_Roadmap_8-1-14.pdf


Reply to Martin Nicholson
The Australian data is based on 70m mast height. Most new turbines are available with mast heights from 80-110m and a few up to 140m. Depending on the terrain, wind speeds at 120-140m can be 15-20% higher than at 70m.

Current class 3 designs are optimised for 6m/min wind speeds and there are models for even lower wind speeds.

Low wind turbine designs are optimised for some production at medium to low speeds rather than peak production at strong winds. This means the Su kW/sq.m of swept area is falling whereas previously a high Su was considered a mark of high efficiency I think the best number was around 2.5, It is now trending towards 6. The
effect is that capacity factors are climbing so that the NREL predicts CF will reach 60% or more in large areas of the US
Taking these three trends together there is ample area of Australia for the 13-15,000 wind turbines we would need. By comparison the area covered by the NEM (not including outback areas) is about 4-5 times the area of Germany and they already have nearly 28,000 wind turbines. Or Texas which is about half the area of the NEM is aiming for similar wind capacity

This is not a suggestion for 100% or even 60% wind, it is just that the technical/economical share for wind is noticeably higher than it was even 3 years ago


Peter Lang.

“I’d suggest the least cost option to provide electricity with about the same emissions intensity as France’s electricity (i.e. less than 10% of Australia’s)”.

From memory Australia’s emissions intensity for electricity is 850gms/kWh, France achieved 40gms in 2014 so their emissions are less than 5% of ours.


Thanks John Morgan for some facts.
The Capacity Factor that you refer to is very important and I think that it is being misunderstood by some contributors. What is being said here is that the total installed capacity for wind is 3752 MW and the peak amount of power generated was 3238 MW. It is not stated how long this peak was achieved for. It may have only been for 5 minutes according to the data that was analysed. John Morgan further says that it is basically impossible for the wind generation system to ever exceed this ratio of 86 percent (3238 MW / 3752 MW). This is an inbuilt inefficiency in a wind generating system.
The capacity factor that others are talking about is plant availability.
With Coal, Gas, Biomass, Diesel, Nuclear, Hydro, Geothermal etc when I call for full power I get the name plate capacity for a defined period of time with Certainty. Because these are all machines they require maintenance and they will never achieve 100 percent availability but when they are available they will give me 100 per cent of name plate capacity.
It is also important to note that the raw data is provided in 5 minute intervals. Grid managers are expected to supply 100 percent of demand on a minute by minute basis.

Blacking out any section of the grid due to a lack of supply is just not acceptable. One might regard certainty of supply as a determinant of a Developed Economy.

I remember watching a TV documentary about the North American Electricity Grid. They were showing the system control room in California and talking about the amount of wind power being generated and showing all the wind turbines in the Colombia River Valley revolving around majestically.
However, within the hour the supply of wind power fell from 2GW to 200mw.
I remember thinking to myself that there must have been a conversation going on somewhere in California similar to a Star Trek Movie.

Kirk ‘Scotty give me everything you’ve got now !!!!!!’

Scotty ‘ Aye captain I already am ! I canne give ye any more!!!!!!’


Thanks everyone for the very interesting discussion in the comments here, all very thought provoking contributions!

Peter Lang, great opening comments, all well put and well taken.

Jim Baerg, I don’t know of any such analysis of solar and demand but the latitudinal variation is an interesting question.

I would really have liked to have included analysis of solar in this post at the same level as wind. Unfortunately, most solar in Australia happens behind the meter, as rooftop PV, so most solar generation does not get reported out to AEMO. The solar data that is reported by AEMO comes from grid scale solar farms, of which there are only a few operating, and not very large. So any solar analysis based on AEMO data would really just be a couple of sites – not enough to draw any broader insight from, so I chose not to analyse it.

Solar PV data that includes rooftop solar does exist, but is created by a process of inference and modelling rather than direct measurement, and, more importantly, is a proprietary product that I’m not about to pay for. If anyone has any suggestions as to where to find a complementary dataset for Australian solar at a similar resolution to this wind data please let me know.

Edward Greisch, you might be interested to read my previous piece on batteries: The Catch-22 of Energy Storage

I should note the obvious qualifications: this data is for Australia, and other parts of the world may show different patterns. Within Australia, most wind is installed in South Australia, so this data is weighted with a high representation from a particular region in the coastal southeast. As wind penetration grows in other states different patterns may emerge (or disappear).

The 29% (or 33%) capacity factor of wind is in fact an unrealisable upper bound on wind penetration. I focus on that bound, set by overgeneration, in this post for reasons of clarity. But there are of course many other limiting factors, some of which have been mentioned in discussion. In particular, Jesse Jenkins and Alex Trembath in their article suggest that only 55%-60% of grid energy could be replaced by variable sources, due to the need to retain significant synchronous generator contribution for frequency control. This means VRE share will struggle to exceed 60% of capacity factor. If that figure is reasonable, then wind would be limited to about 20% (with no solar).


To Peter Lang

I stand corrected, I had assumed peak demand was in the order of 50 GW, so both quantities are oversized. Scaling the installations down and using current costs and allowing for the lower O&M costs of renewables the investments are of a similar value. According to the latest figures I have,renewables would be cheaper, but other posters on this site of course disagree violently.

Re capacity factors, you may not accept my figures but they are not my figures, they are from the US Energy Information Agency, The French Energy Directorate and the US NREL .

The question is, which technology will have the faster learning curve. The market, today does not agree with your choice, but in two or five years who knows.


To Andrew Lang,

I did not say all power plants, I said all power sources, I probably should have been clearer and said all significant power sources. Minimum demand on the NEM seems to be 20% or less than peak so if a source of infinite reliability exceeds 20% of the demand some of it must be dialed down reducing capacity factors.

This is why France’s Nuclear power system runs at 70% or so CF at 75% or so of total generation. In the US where generation is only a bit under 20% of the total, CF is around 90%. According to my sources at the highest levels in the NRC, French technology was generally regarded as being at least as good, if not better than in the US so it is not technology differences that account for the difference in nuclear CF. if the US makes a significant increase in nuclear, its CF will also trend down .

I am not against biomass, in fact I think it is a key part of the system but it shouldn’t be mandated in preference to all other low carbon solutions. Requiring that MSW generators get preference is just as objectionable, if not more so than demanding other generators shut down so wind power gets to sell all available generation at a high price.

While in Australia there are places where heat and power are required, there are many fewer opportunities to economically use the waste heat than in Europe so the optimum amount of biomass is probably lower than in Sweden.


To Peter Farley, I accept your point. But the scope for Waste to energy (fuelled by non-recyclable flammable municipal wastes) is of the order of 1500 MW-e in Eastern Australia. This may or may not rate as ‘significant’.
But it is certainly a fuel source in constant supply and is an unusual power source in that of all sources it is the least able to be flexible in output due to the requirement for furnaces to be operating within very tight parameters – so it is even more ‘baseload’ than brown coal-fuelled plants. But since this power source fully displaces coal-fired plants it is in a diferent category to wind power which does not displace fossil fuels, from the viewpoint of receiving some set feed-in tariff payment.

Regarding the use of heat generated, since each WtE plant is unlikely to be producing over 100 MW of heat (and strangely you don’t hear the term ‘waste heat’ in most of Europe as sale of heat is a major part of the revenue stream of such plants) it is quite feasible to have this go to supply heat needs of nearby industry that have a year-round requirement for it – regardless of our latitude, paper recycling, biofuels production, food processing, industrial laundries, and many other industries, are presently under pressure due to increasing cost of natural gas. For many it is their main input cost along with labour.


Interesting post John … especially the cool bit about weather patterns. Your collection of posts and those of Jenkins and Trembath constitute a powerful demonstration that renewables can only ever be a smallish part of a total solution … not the whole story.


Peter Farley,

According to the latest figures I have, renewables would be cheaper, …

Re capacity factors, you may not accept my figures but they are not my figures, they are from the US Energy Information Agency, The French Energy Directorate and the US NREL.

I don’t know what figures you are using, for what year, what proportion of each technology, what learning rates, for what grid, etc. You have to define the assumptions, use figures that are consistent for all scenarios and all technologies, define the demand profile, and calculate costs applicable for the capacity factors you’ve used in your analyses not the capacity factors used for calculating LCOE for comparing across technologies. If you don’t layout all your assumptions and do analyses on an equivalent basis, the numbers are meaningless. You also need to include grid capital and O&M costs for all technologies.

You can calculate costs for Australia for each technology for the capacity factor for the scenario you are analysing using the AETA calculator which you can obtain from here:

You can estimate grid costs for each technology using this (or go to the OECD source document linked):

If you run these CSIRO calculators you’ll find that nuclear is a much cheaper option than renewables to achieve major cuts in CO2 emissions.



See the cost comparisons at Figure 6 here:
The basis of estimate, method of calculation and assumptions are explained.

Here is a neat chart plotting countries CO2 emissions intensity versus cost of electricity: (go to slide 10 in the slide presentation). Countries with a high proportion of nuclear have much lower GHG emissions intensity and cost of electricity than countries with a high proportion of intermittent renewables. (Also note the irony in slide 14 – which is what you are advocating).

If you want to make a persuasive argument that renewables can substantially reduce Australia’s GHG emissions intensity of electricity, you have an enormous task ahead of you.


Just a quick question for John Morgan. The minimum wind speed has been mentioned for wind turbines. I have heard that there is also a maximum speed at which Turbines stop operating for mechanical reasons. Do you have any information in relation to this?


To avoid getting caught in the mis-construed pro-con discussion of capacity factor applied to power capacity (% of MW nameplate power delivered over a long period), industry participants would be better served if they spoke about energy (in MWh) rather than power (in MW). Electrical engineers, market participants and investors care about MWh because that is the unit they get paid for. Knowing a solar, wind, biomass, hydro, gas or coal-fired plant’s annual energy production in MWh allows for an apples-to-apples comparison, and dividing capex or opex or revenue by the MWh production figure gives pundits an appropriate metric for useful discussion. Better to avoid talking in MW and capacity factors . . it just confuses people.


Geoff Russell

I think you jump the gun.

Capacity factors is on the rise for wind power and solar power as well. So the future number is not 29% penetration or 33% penetration corrected for the Australian wind distribution. Peter Farley has already linked to the the recent NREL study that anticipate wind capacity factors up to 65% by just moving the hub height to 140 meters to 80 meters. A lot of other technologies that is also increasing wind capacity factors is constantly being developed, tested and integrated in new wind turbines. And some even as retrofit to older wind turbines. The number of researchers and engineers that work with refining wind technology and the number of major industrial corporations in the business suggest that the competition is strong and progress will continue.

Cost for both wind and solar is coming down fast and is projected to keep doing so for a long time. The drop in the cost of wind energy dropped last year to only 6% “year on year” after five consecutive years with average 15% cost drop. As solar now has a larger marketshare measured in capacity sold, wind power is forced to press margins.

Storage is a big thing in USA among venture capitalist and also a focus for government grants. The benchmark for storage is to become cheaper than fracking gas peak power plants. John Morgan is an expert in the field so he could probably evaluate whether or not the optimism among storage developers is justified and whether the $100/kWh threshold will be breached in this decade.

Simpler storage where you do not store electrons but just convert electricity to products or heat is also a feasible strategy and probably one that John Morgan studies being an entrepreneur within smart grid technologies.

The obvious long term target for the wind and solar industries and indeed any industry fiddling with CO2 light electricity generation technology is to out compete crude oil, coal and gas altogether.

John Morgan has written a well argued piece on this very subject here on Brawenewclimate and the concept has been around for many decades. What is different now is that wind and solar is now so cheap that the concept is becoming more and more realistic. Nuclear too can potentially reach out for the needed sub US cent price point per kWh.

Ps. The article is well researched and very matter of factly about the present conditions in Australia but the theoretic framework provided by Jenkins and Trembath is not too impressive.


John Morgan,
“Possibly wind blows harder when clouds block sunlight. Unfortunately I don’t have a dataset for solar PV output and can’t test this. My guess is that the number of days and the number of sites at which such anticorrelation occurs is not large enough to shift the average output of the total fleet enough to change the overall picture.”
It sounds as if when you made that guess you were unaware that it’s usually sunnier when air pressure is high and windier when air pressure is low. Yet I posted that objection last time. Did you miss it?

“The economic drag incurred by dealing with surplus generation by storage, curtailment or demand reduction undermines the economics of building additional capacity.”
You don’t deal with surplus generation by demand reduction, you deal with it by demand induction! Do you consider that to be an economic drag? Or an economic boost?

“The capacity of wind and solar is thus limited to be roughly numerically equal to 100% of grid demand.”
Didn’t I explain last time why this was not so? If we accept it going over demand 1% of the time, the decline in profitability is likely to be less than 1% (though it’s hard to predict, as more money is made at times when prices are high than when they’re low). But the capacity would have to increase by far more than 1% to exceed demand.

I remind you of what I said last time:
I suggest you have another look at the graph you got from Hirth: it clearly shows the combination of wind and solar depressing prices less than wind only at the same overall market share. So if Hirth is right, surely that proves that your original argument is wrong?

I also remind you of something else I said last time: there is no Catch22 of renewable energy storage. I am still willing to debate this with you at a site of your choice, though preferably not this one as the mods here are so overenthusiastic that they wouldn’t even let me say what I really thought of it.
As per BNC Comments Policy please supply references for your contentions. BNC is a science based blog which expects that commenters support their opinions with links/refs/data. Otherwise it is just your opinion not fact. Thank you.



All systems are subject to the law of diminishing returns or lower incremental value whichever way you want to express it. If there
was one 6MW wind turbine or one 50MWe waste to energy plant on the system all its power could be absorbed whenever it was generating. Similarly if there was one 1.1GW nuclear power station in the Hunter Valley it would have little difficulty selling its power, however once the capacity of any source increases there would be more and more likely that on some days it cannot sell its power, that is not a big problem for open cycle gas or existing hydro because their daily fixed costs are very low. It is a big problem for coal, even bigger for wind and very large for nuclear because their ongoing capital and overheads are very large.

Lets assume for the sake of the argument that we have 2GW of biomass 1GW which is running @90-98% CF and the rest load following to some extent so the average output is 1.5GW.
Then we have 8GW of hydro and there are a few plants which can be expanded and one or two more which can be built so we have 10GW peak of hydro. Then if wind farms use high Su turbines and are spread over a wider area then we can count on 3-4GW of wind.

Peaks occur in the late afternoon and so we can only assume 2-3GW of solar so now we have a total of renewables of around 18GW so if the peak demand is 25 we need 7-12 GW of nuclear or storage of some sort to cover the peak.

Whatever technology you use, you get to a point where further investment in a particular type of technology becomes uneconomic. Nuclear and biomass have a higher value because they are dispatchable but even so, no-one is going to build a nuclear, biomass or geothermal plant to cover the last 5-10% of peak demand so you have a choice of gas, hydro or storage.

There is no single metric that you can use to find the best solution. Even if wind or solar LCOE was half the next best choice it doesn’t cut it if there is no wind one night. The LCOE of open cycle gas is very high yet people build plants and make money because of their fast ramping, high value peak output. Hydro is great except for the next big drought and nuclear is great as long as demand is highly predictable 10-15 years out and no-one finds a generic fault in the fleet of SMR’s you installed 10 years ago and energy efficiency and LED lighting don’t blow away you spring and autumn demand.

My premise is that Low carbon is essential, distributed generation is good, “Short time to light” is good. Scalability is good. LCOE is important and technological variety is also good. Of course high availability is critical and that favours gas, biomass and nuclear whereas scalability, and time to light favour wind and solar.


Interesting analysis John, thanks for sharing. I also spend a bit of time looking at wind data, and notice I have a few differences to you. It would be good to clarify them. The main point of difference is that I get an average capacity factor for the period (1/9/2014-31/8/15?) of 32.6%, compared to your 29% value. I think there are a couple of reasons for this discrepancy.

I notice you have an nameplate capacity of 3753 MW. This seems a little on the high side – the AEMO generator list (link below) totals 3667 MW of wind. However AEMO’s list includes Codrington, Hepburn, Toora, Windy Hill & Wonthaggi, which as far as I’m aware, AEMO doesn’t provide the data for these (though please let me know if you have found this data). Are you including these wind farms (67 MW) in your installed capacity, but not in the average power output calculations?
In calculating the average capacity factor, you’ve assumed the entire 3753 MW was installed for the entire year. However, several wind farms were still under construction during the year of interest, and thus weren’t at full power for the full year. These wind farms were Portland, Bald Hills, Boco Rock, Gullen Range, & Taralga. I’ve estimated the installed capacity of these projects for each month of the year in question, and once I’ve averaged the 12 months, I get an average installed capacity that is 150 MW less than the final installed capacity.

Also, thanks for making the point that when looking at rule-of-thumb penetration limits for renewables, the fact that the entire fleet of wind is never at full power simultaneously means the capacity factor rule-of-thumb can likely be exceeded without curtailment. This is also important for solar, as the Australian fleet output for solar also rarely exceeds 75%, as indicated in live output from the live solar output from APVI.

Moreover, I think once you incorporate solar output to the wind output, the max combined output will be significantly less than the max wind output added to the max solar output. Indeed, for the year in question, the max output of wind occurred during July. Presumably solar output will peak during the months of Oct-Feb. The peak wind output in these months is about 16% less than the July wind peak during this year of interest.

regards, Dave Osmond


Peter Farley,

My premise is that Low carbon is essential, distributed generation is good, “Short time to light” is good. Scalability is good. LCOE is important and technological variety is also good. Of course high availability is critical and that favours gas, biomass and nuclear whereas scalability, and time to light favour wind and solar.

These are a statement of your personal beliefs and preferences. They are not those demonstrated by preferences expressed through market choices and they are not the requirements of the electricity system. The primary and secondary requirements of the energy system are:

Energy supply requirements

The most important requirements for energy supply are:

Energy security (refers to the long term; it is especially relevant for extended periods of economic and trade disputes or military disruptions that could threaten energy supply, e.g. 1970’s oil crises, world wars, Russia cuts off gas supplies to Europe).
Reliability of supply (over periods of minutes, hours, days, weeks – e.g. NE USA and Canada 1965 and 2003)
Low cost energy – energy is a fundamental input to everything humans have; if we increase the cost of energy we retard the rate of improvement of human well-being.

Policies must deliver the above three essential requirements. Lower priority requirements are:

Health and safety
Environmentally benign

Why health and safety and environmental impacts are lower priority requirements than energy security, reliability and cost

This ranking of the criteria is what consumers demonstrate in their choices. They’d prefer to have dirty energy than no energy. Electricity is orders of magnitude safer and healthier than burning dung for cooking and heating inside a hut. The choice is clear. The order of the criteria is demonstrated all over the world over thousands of years – any energy is better than no energy.

Nuclear can meet these requirements much better and much cheaper than non-dispatchable ‘renewable’ energy. Renewables cannot make much of a contribution to meeting the requirements or to reducing global GHG emissions. (For more see the links in my previous reply to you).


Dave Osmond,

Dr Wheatley’s analysis of the AEMO data for calendar year 2014 gave an capacity factor of 29%. I understand his analysis used the average installed capacity of wind farms in operation in 2014.

His analysis was done for a submission to the the Senate Select Committee on Wind Turbines. You can access it from the Senate site, Submission No. 348 , or more easily from his web site:

Anyone interested in the topic of this thread is encouraged to read read this very thorough and excellent analysis.


Wheatley’s analysis has the same issue. He used the installed wind capacity at the end of 2014, 3394 MW, and assumed it was available for the entire year. As it turns out, an average of only 3105 MW was available, if you average the values for each of the 12 months. This brings the average capacity factor up to 31.2%


Thanks for your kind words this morning Peter Lang.

To respond to three main distinct parts to your posts.

Capacity factors. It appears that John Morgan and myself are likely to soon be in close agreement on CFs for Sep 2014-Sep 2015. My main point for arguing this is that many people seem to think wind capacity factors in Australia are in the 15-30% range, and moreover believe wind penetration rates on the NEM will never exceed the wind CF. To those people I hope you now understand that the national annual average wind CF in Australia average around 30%-37% (there’s variation from year to year, and note that CFs from the relatively modern wind farms in WA are the highest in the nation, not that that helps us on the NEM). I also hope that people realise that it is easy to calculate a misleadingly low CF for wind farms if you do not allow for the fact that a wind farm may have started generating in the 2nd half of the year (ie, generation data may not represent a full year of operation), and also that a wind farm often starts generating once just a handful of turbines are operating, and there is sometimes up to a year delay before the final turbines start generating (ie, the data may not represent a complete year of operation from the entire project).

To those who believe that penetration rates from wind or solar will never exceed their CF, please note that instead of using CF, you should instead use annual average power/ annual maximum power. This is a point John Morgan made in the article above. For distributed, NEM-wide wind, maximum power is likely to be atleast 10% lower than installed capacity. For residential solar, NEM-wide maximum power is likely to be atleast 20% lower than installed (DC) capacity. And note that a small amount of storage or curtailment can (if required) easily reduce the maximum power output further, and that demand is significantly higher than average when PV hits max output.

And finally, although many of the best, windiest sites may have already been developed, modern Class III wind turbines with high hub-heights and large rotors can achieve higher CFs than these existing wind farms in their windier sites (ie, lower turbine Su as Peter Farley has mentioned).

Peter Lang, I cannot provide a link to an AEMO document indicating that Wheatley’s CFs are wrong, particularly for NSW. I have simply downloaded the data from AEMO as John Morgan did, and have analysed the data for myself. If you want to message Wheatley, I suggest you ask, when calculating the CFs for NSW (and for the entire NEM), if he allowed for the fact that Taralga only started generating in December 2014, and also that Gullen was under construction for most of the year, and only reached full capacity in December.

Wind CO2 abatement effectiveness. I don’t think I can add to my previous comments regarding Wheatley’s paper, other than to agree that wind C02 abatement effectiveness is likely to decrease with wind penetration rate. I believe Wheatley’s paper is fatally flawed in calculating the current effectiveness of wind on the NEM. Long-term South Australia data clearly shows that wind has displaced far more coal generation in SA than gas generation, in clear contradiction to Wheatley’s paper. And regardless of whether Wheatley’s calculation of abatement effectiveness is wrong or not, an appropriate follow-up question is if any alternative generation could be more effective in abating CO2 in a market where current coal generation is cheaper than gas generation.
Battery costs. You are most likely right that pumped hydro storage costs are cheaper than current battery storage. However, for pumped hydro to be economic using price arbitrage, it must use price differentials on the wholesale electricity market. On a typical day, you are likely to only get a $10-$30/MWh price differential to work with.

However, we currently have over 1.5 million homes with roof-top PV, a number that continues to grow rapidly. Many of these households, in the next year or two, will no longer have access to gross feed-in tarrifs, and will find themselves producing excess generation during the day for which they only get paid ~6c/kWh, while later on in the evening they will be charged ~30c per kWh for grid electricity. They have a ~$240/MWh price differential to work with. With battery pricing proposed for the next year, this is likely to be economic. One million homes times 10 kWh battery is 10 GWh of battery storage. This is enough to reshape the diurnal NEM generation profile. To put this in context, on Jan 16 last year, NEM demand hit a multi-year peak of 33 GW. Average demand for the day was about 27 GW. About 50 GWh of storage could have reduced that daily peak to the daily average of 27 GW, a saving of 6 GW of peaking generating capacity. About 30 GWh of storage could have reduced the daily peak to 29 GW, saving 4 GW of generating capacity.


Some more comments on Dr Wheatley’s paper. I agree Wheatley’s paper is very thorough. Unfortunately it is highly misleading, and I also believe it to be fundamentally wrong.

The paper claims wind is only 78% effective in reducing emissions. This is because the paper claims wind power makes up 4.5% of generation, but only reduces emissions by 3.5%. However, this effectiveness is highly misleading. Any new power station is likely to displace other generation with the highest marginal cost, which in most cases is gas. Consider building a new near zero-emission generator (wind, solar or nuclear) in Sth Australia (which is the state that has seen the most wind built). This generator is likely to mostly displace gas generation (the highest cost generator in SA), with an average CO2 intensity of about 0.6 tCO2/MWh. If this new generator supplied 1% of NEM demand, it would reduce emissions by about 0.7%. According to Wheatley’s definition, it would have an effectiveness rate of about 70%. In comparison, Wheatley’s determination that NEM wind was 78% effective illustrates that it actually did quite OK. To have effectiveness greater than 100%, you would either need coal to have a higher marginal cost than gas, or you’d need some other mechanism to reduce coal generation instead of gas.

I also believe Wheatley’s paper to be fundamentally wrong, as it uses correlation analysis on a 5 minute time scale to determine what wind is displacing. However, what wind displaces on a 5 minute timescale is completely different to what it displaces over the longer term. On a 5 minute basis, Wheatley determined that wind displaced 5 times more gas than coal. This is not surprising, coal generation is unlikely to respond to short timescale fluctuations in the wind. However, the figure in the following article illustrates the long-term changes are completely different. There’s been very little trend in gas generation in SA since 2005. In contrast, there’s been a very strong decline in coal as it is displaced by the rapid increase in wind generation. So at the risk of appearing to contradict what I said in the previous paragraph, it appears that wind has successfully displaced coal in South Australia. Obviously this was helped by the declining quality and availability of coal in SA.


Dave Osmond,

Thank you for that information. I see the first line of Section 2.1 of Wheatley’s report says:

Wind provided 8.7TWh in 2014 or 4.5% of total energy generated. SCADA data is available for 34 wind farms with total installed capacity of 3394MW

I understood that figure was the average installed capacity for calendar year 2014. You may be correct and the figures is not right, but I’d like to be able to check for the source data for myself. I haven’t found the installed capacities and commissioning dates on the “Registration and Exemption List” you linked here: .

Can you give me a link to the source data for the installed wind capacity at start of 2014 and the capacity that was added and the commissioning dates through the year? Or a schedule of the installed capacity by month through the year, or whatever the basis was for the calculation of 3104 MW average installed capacity through calendar year 2014.

For capacity factor we need the installed capacity of wind farms, not just those that are available. We have to be consistent with how capacity factors are estimated for all other technologies.


Sorry, here’s a link to the figure of the article.

Y axis is proportion of SA demand coming from each type.
Peter Lang, I will hopefully be able to provide the information you’re after tomorrow.


Tony Carden,

I have heard that there is also a maximum speed at which Turbines stop operating for mechanical reasons. Do you have any information in relation to this?

Good question, and I’m not across the details of the mechanical engineering of wind turbines so I have no particular insight. I imagine both the bending moments of the blades at the point of attachment to the nosecone, and the unbalanced axial loads transferred to the driveshaft and bearings, must become enormous as wind speed increases. I’d also be interested if others know more about this.


Tony Carden my understanding is that all turbines have an rpm that is the limit at which blades start to feather – this is reached usually around windspeed of13-15 m/s, and at around 25 m/s they will brake and stop. So rated output of the nameplate capacity is being produced at this rpm (often around 15-16 rpm but differs for each make and rotor diameter). This information is given by the manufacturer along with the curve of output against windspeed.


John Morgan, I have done some quick analysis comparing timing of low wind generation days with low solar generation days. For this analysis, I have looked at 2 years of solar and wind data, Nov 2013-Nov 2015.

For solar generation data, I have used daily generation data from the website, collecting data from a variety of systems in the NEM state capitals. I combined them by weighting their output in proportion to state demand. Average CF of my data was 17.7%, which is probably on the high side (NEM average residential is more like 15.4%).

For wind generation, I used all NEM wind farm data. Average CF was 31.3%, a little on the low side as I hadn’t fully corrected for all wind farms under construction.

I define a low generation day as one where the average daily CF was less than 10%. 4.3% of days were low generation according to the PV data. 4.7% were low generation according to the wind data. If you add the wind output to the solar output (in a ratio of 60%:40% solar:wind by installed capacity), and recalculate the daily CFs (average=23%), then you find that less than 1% of days are low generation when you use a mixture of wind and solar. This means that it is quite rare for a day to have both very low solar generation and very low wind generation. Indeed, only about 1/5 of the low solar days were also low wind (or vice-versa).

This emphasises the point of some research I’ve previously done, and also matches up with AEMO, UNSW and BZE renewable studies. Storage requirements for a high-renewable penetration electricity grid in Australia will be much lower if you use a good mixture of wind and solar, rather than letting one or the other dominate.


I think that there is another important fact to consider.
There are also upper limits on how much wind is useful.
For example if Australia has 30GW of wind capacity, from the facts that John Morgan has analysed we can expect to get approx 10 GW generated in a year. But we also need to consider the peaks generated. On some days and we do not necessarily know the time of day when it will occur we may generate 25.8 GW at peak (86% of 30GW from John Morgans figures above). If the amount being supplied by VRE’s at a given point in time exceeds total grid demand what do we do with it. Shut down all our Base Load power to use the so-called free power from VRE’s.


If you google “turbine power curve”, plus the name of the turbine, and look at the images, you should be able to see what the shut down (cut-out) speed is for various turbines.

Most turbines cut-out at speeds of around 20m/s for a Class III turbine, and 25 m/s for a Class I turbine, and somewhere in between for a Class II turbine. Class I turbines are designed for windy sites, generally with an average wind speed > 8.5m/s, while Class III turbines are typically for sites with average speed < 7.5m/s (Class II turbines obviously between those 2 values).

This brings us back to the point that Jens S and Peter F have been making. There have been rapid developments in Class III turbines in recent years, in addition to a general move in the industry from Class I to Class III turbines. This is because new sites are generally less windy than those developed a decade ago. A Class III turbine will achieve a much higher capacity factor than a Class I turbine at a given site, as it will have a higher swept area to generator size ratio. It will achieve rated capacity at a lower wind speed. This also means it has a lower efficiency at the higher wind speeds, but at a low wind speed site, this is less important. There is a lot less force on a turbine if it is shut down at higher wind speeds, so this means that a Class III turbine can be made cheaper, lighter and less strong than a Class I turbine, obviously at the cost of generating less power at these higher wind speeds.


Aidan Stanger,

It sounds as if when you made that guess you were unaware that it’s usually sunnier when air pressure is high and windier when air pressure is low. Yet I posted that objection last time. Did you miss it?

Indeed I did not, for I responded to it on that thread here.

I heard on that thread that wind and solar are anticorrelated across:

*summer / winter
*day / night and afternoons / mornings / midday
*and with weather.

These were offered without data. The data above shows first two contentions are wrong. You are now advancing the third, again without data. I would say that you are guessing too.

Yes, there are windy storms and calm sunny days. There are also sunny days with wind (like today), and days and weeks where the rain sets in and wind is low. There are advancing storm fronts that drive wind in sun ahead of a breaking storm.

Where is your data to show wind and sun are anticorrelated, at what time resolution, and for what fraction of the time? How do you determine that this happens for a significant fraction of the time? Does it rain more in the afternoons, or at night time, or midday? If so, there’s no correlation between wind and rain because the day-by-hour analysis shows nothing. Maybe cloudy rainless wind occurs to a sufficiently large degree to shift the conclusions. But now you’re relying on weather to cooperate with your argument.

I don’t buy it. Bring me the data.

You don’t deal with surplus generation by demand reduction, you deal with it by demand induction! Do you consider that to be an economic drag? Or an economic boost?

Quite so. I meant to write “demand management”. Good catch. I regard it as an economic drag, because you are asking energy consumers to behave contrary to their default energy usage. This is the grid requesting a service from controllable loads, and the owners of such loads request payment for this service.

“The capacity of wind and solar is thus limited to be roughly numerically equal to 100% of grid demand.”
Didn’t I explain last time why this was not so?

Not in any way I found compelling. I’d point out that I have not dwelt on limits that cut in before this 100% demand share either, in particular the requirement to spill (etc.) well before 100% of demand is reached by wind and solar in order to retain sufficient share of synchronous generation for frequency control.

I remind you of what I said last time:
I suggest you have another look at the graph you got from Hirth: it clearly shows the combination of wind and solar depressing prices less than wind only at the same overall market share.

No, it doesn’t. I explained how this worked in this comment. Hirth’s data does not show wind and solar depressing prices, it show depressing value factors of wind, and wind and solar in combination. It is not presented in a way that allows a direct test of the thesis, but I was able to slice the data through two data points that did allow such a test, which I annotated the graph with, and which do support the thesis.

the mods here are so overenthusiastic that they wouldn’t even let me say what I really thought of it.

Your last comment on that question was deleted as abusive before I saw it. Quite frankly I was grateful to the mods for sparing me from having to read it.


Dave Osmond

Instead of assuming that wind compete against natural gas power plants you should understand the point that John Morgan makes about the needed natural gas back up for wind power. And if this is not convincing you should look at the actual development in markets with wind power penetration closing in on the capacity factor limitation also argued by John Morgan. In these market the power generation that is made obsolete when wind power is introduced is slow coal power plants.

Peter Lang and others argues that wind power has an issue with grid integration cost whereof some of these grid integration cost should be directed to peak power plants.

Logically the attribution of cost and the attribution of CO2 abatement effect should follow each other. If you follow logics and the real life observed decline of coal power plants capacity factor when wind penetration rise with associated natural gas peak power plant penetration then you should factor the combined wind/gas CO2 abatement effect in as 100% of what the substituted coal power plants consumed minus the CO2 emission from the wind/gas solution. The usual decision making when coal power plants are being made obsolete is to take those coal power plants that has the largest running costs offline first, which is almost always the oldest and least effective coal plants, so the CO2 abatement effect is almost always higher than the average CO2 emission from coal power on the grid where wind/gas substitute coal power.

Coal power plants that ramp up and down fast has considerably lower than achievable efficiency. With wind/gas on the grid coal power plants can most of the time be driven with less variation and slower ramp up and can even be moth balled in seasons where their output is not required.

These better driving strategies for coal power plants further increase the positive result of a logics and fact based CO2 abatement calculation.

Finally and very relevant many places on earth the pull on fresh water reserves and seawater resources release any GHG they may contain including water vapor and especially for fresh water the cooling water consumption may impact hydropower and or irrigation and thus respectively decrease hydro power output and limit carbon capture in plants and soil.

On the down side coal power plants are run by businesses that could not care less about CO2 abatement so they will always try to supply all they got when there is are a margin to be earned. Further if the waste heat is used for district heating or process heat they may have obligations that oblige them to run even at times where they have negative margins on the electricity they can sell.

In conclusion your comment about the unlikely achievability of more than 100% CO2 abatement effect is probably wrong. Wind/gas can achieve more than 100% CO2 abatement effect in real life conditions.

As for your comments about the actual capacity factor I do not think that there has been any attempt to tinker creatively with the numbers. I think John Morgan is fully aware of the development in wind power and the ongoing increase in capacity factors as well as the accompanied decrease in LCOE since his business focus upon innovations within grid scale storage and smart grid.

Ps. Thumbs up for your correct thrashing of the Wheatley paper where you indadvertedly deliver some of the logical arguments supporting why we in the marketplace see a rise in wind/natural gas and a decline in coal power, which both I and John Morgan have already made.


John Morgan,
The correlation between sunshine and high pressure is easily explained: in low pressure conditions the air rises, therefore cools, therefore clouds form as the water vapour in the air condenses. Whereas in high pressure conditions, air falls, therefore warms, so it’s not conducive to cloud formation and clouds can even evaporate. Is that clear enough or do you require a link?

The link between wind and low pressure I’m not quite so clear on. Wind is stronger where the pressure gradient is stronger. The pressure gradient is usually stronger in low pressure conditions. I admit I’m not sure quite why that is, but the relationship is clear – see

“Does it rain more in the afternoons, or at night time, or midday?”
In equatorial regions it rains more in the afternoons because of convectional uplift. Elsewhere I’m not aware of any difference.

“I regard it as an economic drag, because you are asking energy consumers to behave contrary to their default energy usage. This is the grid requesting a service from controllable loads, and the owners of such loads request payment for this service.”
The way I see it, it’s an economic boost, because it gives electricity consumers the opportunity to save money by changing their energy usage pattern to take advantage of cheaper electricity. Why do you not see it like that?

“Not in any way I found compelling. I’d point out that I have not dwelt on limits that cut in before this 100% demand share either, in particular the requirement to spill (etc.) well before 100% of demand is reached by wind and solar in order to retain sufficient share of synchronous generation for frequency control.”
But many of the wind turbines do synchronous generation. And synchronous generation isn’t the only means of frequency control. Some places use flywheel storage for that purpose (I’m not going to hunt the link right now, but I can find it tomorrow if you’re interested). I expect it’s also possible to do it purely electronically; are there any electrical engineers here who can confirm or refute that?

“Hirth’s data does not show wind and solar depressing prices, it show depressing value factors of wind, and wind and solar in combination. It is not presented in a way that allows a direct test of the thesis, but I was able to slice the data through two data points that did allow such a test, which I annotated the graph with, and which do support the thesis.”
If the proportion of solar really is “matching” then you pointed out that 10% wind + 10% solar depresses the value factor more than 10% wind alone. Which is so obvious that I’m surprised you thought it needed highlighting. But if you look at the same RES market share, you’ll see that the Solar and Wind curve is above the Wind Only curve; it depresses the value factor less. Were the Less Than The Sum Of Its Parts hypothesis correct, the Solar and Wind curve would be below the Wind Only curve, as it would depress the value factor more.


David Osmond,

Thank you for your comment. Critiques are valuable.

However, I think you have misunderstood what CO2 abatement effectiveness means. It is “ratio of % CO2 emissions savings to % wind power generation”. Another way to think of it is: if the average CO2-e emissions intensity of the grid is 1 t/MWh and wind energy saves 0.8 t/MWh, the abatement effectiveness is 80%. If wind energy saves 1.2 t/MWh, as would be the case if it displaced generation from high emissions intensity brown coal generation, the abatement effectiveness would be 120%.

Abatement effectiveness decreases as wind energy penetration increases – unless there are significant other factors changing the dispatch order of the technologies in the grid. ERCOT is an example where this has been occurring. The abatement effectiveness of wind has been increasing because the cost of gas has been reducing relative to the cost of coal. So there has been a move towards gas generators becoming the baseload generator and coal becoming the intermediate generators. Coals is ramping and cycling more in ERCOT now than was the case when gas was more expensive. However, that is not the case in Australia, and unlikely to happen any time in the foreseeable future. In fact gas prices are projected to increase, not decrease relative to coal.

Your chart of proportion of South Australia’s generation from each type of generator (i.e. fuel type), shows declining coal proportion as wind proportion increases. But this is not a plot of abatement effectiveness. A plot of abatement effectiveness for these years would almost certainly show that effectiveness decreases as the proportion of wind generation increases. This is significant because it means the estimates of CO2 abatement cost are underestimates and increasingly so as wind penetration increases. The chart of Herbert Inhaber analysis of many earlier studies of CO2 abatement effectiveness shows the shape of the curve, although we now know there were problems in the Inhaber analysis such that the curve is too low, but the shape seems to be supported by the growing evidence from recent studies such as Wheatley’s for Ireland and Australia and Daniel Kaffine et al. for various US grids.

Ref: “CO2 avoidance cost with wind energy in Australia and carbon price implications

Wheatley’s analysis demonstrates the importance of analysing the whole grid, not just South Australia in isolation. Wind power in South Australia is mainly backed up by cycling and ramping of relatively efficient (high cost) black coal power stations in NSW, rather than brown coal in Victoria. This explains why wind power generation abates less than the average intensity of the grid.


Hi Peter Lang, this is not exactly what you are after, but hopefully it’s sufficient.

If you go to the link below, it will show you wind farms operating on Dec 31, 2014 for which AEMO data is available. It contains all the wind farms in the AEMO register, except Codrington, Hepburn, Toora, Windy Hill & Wonthaggi, for which, as far as I’m aware, AEMO doesn’t provide data. That is 35 wind farms with an installed capacity of 3601 MW. Note the AEMO list has Boco rock (BOCORWWF1) listed twice, I have ignored that duplication, though included the full capacity of 113 MW.

On Dec 31, the anero web site also excludes Bald Hill, which isn’t yet generating. That leaves 34 wind farms with an installed capacity of 3493 MW. If you go back to the beginning of Dec, you will also see Taralga disappear, as it also wasn’t yet generating. I am guessing Wheatley also excluded this wind farm. That leaves 33 wind farms with an installed capacity of 3386 MW, not quite the same as what Wheatley quotes, 34 wind farms with a total capacity of 3394 MW, but the installed capacity is very close, and the Boco rock WF duplication may explain the mismatch in wind farm number.

Now if you go back to Aug 2014, you will also see Boco rock disapear, as it is not yet generating. Now we are down to 3273 MW. Hopefully this is enough to tell you Wheatley’s value is not an average installed capacity for the year.

To explain how I calculate the installed capacity each month for wind farms under construction, for each month I determine the max generation, according to AEMO data, and add 5%. If this is greater than the official registered capacity, then I use that instead, and continue to use that for thereafter, considering that farm is now fully commissioned. To give you some reassurance, it is rare for a modern wind farm to not reach 95% of its installed capacity in any month once it is fully commissioned.

I calculate an installed capacity of 2819 MW at end Jan, 2014, and 3396 MW at end Dec, 2014. The 12 month average for 2014 I get to be 3105 MW.

At the end of Jan 2014, the following wind farms were not yet generating or at full capacity. Bald Hills, Boco Rock, Gullen Range, Mt Mercer, Snowtown 2 Nth & Snowtown 2 Sth

Some more information

Click to access BHWF-Project-Schedule_20aug12.pdf


David Osmond,

Thank you for that explanation. I am not able to download all the required data from AEMO so I cannot check what Wheatley used. But I did ask him if the capacity factors were calculated on the basis of end of year capacity or average capacity for the year and he replied it was average capacity for the year. He was getting all the data from AEMO. He would have correctly used the capacity from commissioning date, and not have subtracted periods where they are out of operation for whatever reason. But we can always make mistakes and there are many errors in AEMO data too.


For those interested in further information on wind farm capacity factors in Australia.

AEMO has provided capacity factors for Sth Australian wind farms in its historical market information report. Fig 7 indicates the average capacity factor for Sth Australian wind farms was 32.7% (not weighted by project size). It also indicates that the average CF was 31.8% during summer and 34.8% during winter (36.2% if you ignore some extremely low CFs resulting from wind farms not yet fully constructed).


Hi John Morgan,

You have an afternoon bias in your definition in solar hours of 10am to 4pm.

Remeber AEMO time is AEST, and does not include daylight savings, so the peak hours should be centred approximately around noon, although solar data from SA will shift that somewhat to after noon.

As your diurnal plots indicate, wind output often picks up in the afternoon after 2pm. If you remove your afternoon bias, and define solar hours 10am-1:59pm or 9am-2:59pm, then you will start to see wind farm output during non-solar hours exceeding those during solar hours. The SA solar data justifies a slight bias to the afternoon, so perhaps 10am:2:59pm or 9am:3:59pm could be reasonable.

Also, my analysis of AEMO data since 2008 indicates wind output is greatest during the months of July, Aug & Sep (CF~37%), and least during the months of Mar, Apr & May (CF~30%). The peak wind months certainly help offset most of the poor solar months in winter. But obviously it would be nice if the wind in May was more productive. I suspect this will be the problem month if we aim to get most of our electricity from wind and solar.


Further points about capacity factor

It is obvious that any excess capacity is an economic drag, but the focus in this debate seems to be on generation rather than demand. To meet peak demand there has to be some capacity that is not fully used all the time

The current Australian grid plus rooftop solar averages a bit under 47% CF. Without rooftop solar it is almost exactly 50%. Almost all assets are the same, cars, trucks, railway lines etc. very few are used at even 90% capacity.

Returning to energy and looking at individual sources nobody seems too upset that hydro CF is around half that of wind because the operating costs are low and the despatchability is high. OCG has very low capital costs very high ramp rates (up and down) but again has a capacity factor anywhere between 10 and 20%. Again nobody complains too much

Conversely when a coal power plant falls below 55% CF or nuclear below about 70% it becomes very difficult to service the fixed costs, interest, staff, depreciation, maintenance, security and the end of life clean up trust fund.

If we plan for peak demand at 35GW with say 8 GW of hydro running at 80% and 5GW of wind and +10GW solar running @5% and biomass at 1.5 @ 85% on a hot still afternoon then we need 26GW of other plus a reserve of 3-4 so alternative sources have a total of 30GW.

Lets say that is all nuclear we then have an annual capacity at their respective capacity factors of 9Tw.hrs hydro (15%), 11 TW.hrs wind (30%), 12 TW.hrs solar (70%), 10 TW.hrs biomass (85%) and 240 TW.hrs of nuclear (90%) i.e generation of 280-290TW.hrs.

However the system only needs about 190TW.hrs so we can’t in fact reach the capacity factors above.

Even if we reduce the biomass by half and in the next parliament we get approval to go nuclear, by the time the first plant is started wind and solar will already reach or exceed the above capacity. The marginal cost of output from wind and solar is much lower than nuclear so either the nuclear plants will give power away or they will generate about 150-160TW.hrs of power therefore having a capacity factor of 60%. So the sensible thing to do is to build about 20-23GW of nuclear @85-90% and 7-10GW of storage/enhanced hydro.

Of course now that we have storage on the system the marginal cost of delivering wind and solar to storage is lower than the marginal cost of nuclear so there is an incentive to build more wind and solar and even less nuclear so the optimum number and generation contribution of nuclear falls further.

All this assumes the worldwide trend to de-industrialisation and higher energy efficiency does not continue or in fact accelerate, which is the most likely scenario. It also assumes continued economic growth in Australia. If a company was borrowing money for a 7-10 year project with a 30 year payback after that time there are some big ifs to overcome.


David Osmond,

Fig 7 indicates the average capacity factor for Sth Australian wind farms was 32.7% (not weighted by project size).

Thank you for the link. It is for several financial years with no total given for SA. I presume you have averaged the numbers but you didn’t say for which year. Wheatley calculated the capacity factor of wind power by state for calendar year 2014 on page 10, as:

Capacity factors at regional level were 19%(NSW), 35% (TAS), 31%(SA) and 28%(VIC).

The capacity factor figure you quoted and Wheatley calculated for South Australia are fairly close and I think arguing about such small differences here is distracting from the important, policy-relevant points which I would summarise as:

Average capacity of factor of wind in the NEM was about 30% in 2014
CO2 abatement effectiveness of wind in the NEM in 2014 was 78%.
This is consistent with the abatement effectiveness in other girds (e.g. ERCOT) with similar proportions of coal,gas and wind generation and similar wind energy penetration.
CO2 abatement effectiveness decreases as wind energy penetration increases.

– Estimates of CO2 abatement cost that assume wind power generation avoids the average emissions intensity of the grid are incorrect. They underestimate CO2 abatement cost in inverse inversel proportion to CO2 abatement effectiveness – e.g. if CO2 abatement effectiveness is 50%, then the CO2 abatement cost is underestimated by a factor for 2 (i.e needs to be increased by 100%.)

This last point is the important policy-relevant issue.


Peter, you suggest that we are only dealing with small differences in capacity factor. However you then quote Wheatley’s claim that wind farms in NSW had a capacity factor of 19%. This clearly illustrates the misleading way he has calculated the capacity factor. The average capacity factor for the NSW wind farms that were fully operational during all of 2014 (Capital, Cullerin, Gunning & Woodlawn) was 29% in 2014.

The only way you could get 19% for NSW is by including both Gullen Range and Taralga wind farms in the totals, and ignoring the fact that Taralga only started to generate in the final month of the year (and even then, less than 25% of the project was operational), and Gullen only reached full capacity in December.

And you repeat Wheatley’s claim that wind is only 78% effective at reducing emissions. A claim which is based on 5 minute correlation analysis suggesting wind displaces 5 times more gas than coal. This claim looks highly dubious after looking at South Australia’s generation since 2005, which indicates wind has displaced much more coal than gas in that state.

Perhaps I can summarise some relevant policy points of my own

average capacity factor of wind generation in the Australia is 34%, based on data from 2008 till end Oct 2015
the average capacity factor of wind in winter is above average at 37%, which will help complement the low capacity factor of solar in those months
data from South Australia has demonstrated that wind can primarily displace coal generation, albeit with the help of interconnector flows from Victoria
even with energy penetration rates of 33%, 5 minute variations in wind generation in South Australia are still less than 5 minute changes in demand, and significantly less than the reserve required to cope with the sudden and unexpected loss of a large coal or gas power station in that state.

For that last point, see Fig 12 in the South Australian wind study report.


David Osmond,

The only way you could get 19% for NSW is by including both Gullen Range and Taralga wind farms in the totals, and ignoring the fact that Taralga only started to generate in the final month of the year (and even then, less than 25% of the project was operational), and Gullen only reached full capacity in December.

I accept Wheatley’s have used incorrect capacity factors or he may have obtained incorrect data from AEMO. But at the moment you haven’t provided the correct data I’d need to be able to send him before I could ask him a question. I can’t just post a comment on his web site telling him he’s wrong. Can you provide the capacity factors for wind generation in each state of the NEM for 2014 and provide links to the AEMO sources to support the figures you provide? I need to be able to reproduce the figures you provide.

And you repeat Wheatley’s claim that wind is only 78% effective at reducing emissions. A claim which is based on 5 minute correlation analysis suggesting wind displaces 5 times more gas than coal. This claim looks highly dubious after looking at South Australia’s generation since 2005, which indicates wind has displaced much more coal than gas in that state.

I did respond (nicely) to this point in an earlier reply to you. I’ll try to be clearer. I think you have misunderstood what CO2 abatement effectiveness means as used in Wheatley’s analysis. It is defined and explained in Wheatley’s submission and I quoted the definition in my previous comment.

Your comment about 5 minute data suggests you not understand how analyses of CO2 emissions avoided by fluctuating-power, intermittent generators are done. These analyses have to use short period data. The shorter the better. 1-minute data would be even better. [However, as an aside, because the 5-minute data is MW as-generated, rather than MWh sent-out and measured at the regional nodes, which is the basis for all the commercial settlements and for AEMO’s calculations of CO2 emissions from the NEM generators, it would be better to use the latter because it is energy. But this data is commercial in confidence and not publically available. It was not available for this study. However, Wheatley estimate any error caused by this would be less than 1%. ]

Your “highly dubious” assertion is your opinion, unsupported by evidence. You haven’t provided what you believe is the correction required nor what you believe the correct values are. If you want to make a constructive critique, it would be more valuable if you detail what corrections need to be made to the analysis and quantify what you believe is the error. It would help if you said how much difference your suggested revisions would make to the CO2 abatement effectiveness of wind generation in the NEM in 2014.

The fact that the calculated CO2 abatement effectiveness in the NEM at 4.5% wind energy penetration is similar to that calculated for ERCOT by Daniel Kaffine et al. when wind energy penetration was 4.7% is a reasonable reality check on Wheatley’s estimate for the NEM. Furthermore, the NEM and ERCOT abatement effectiveness figures fall on the trend line with the figure for Ireland, i.e. 53% effective at 17% wind energy penetration. All in all, the Wheatley calculation of 78% CO2 abatement effectiveness for the NEM at 4.5% wind energy penetration, looks reasonable. It’s recognised, of course, there are always uncertainties, and it would be excellent to reduce them. Wheatley’s report points out what he believes are the main causes of uncertainty in the analyses and what could be done to reduce them. The main one is to get better CO2 emissions data for the few power stations that are responsible for most of the ramping and cycling for backing up for wind power variability.

You could gain a fuller understanding of the analyses by reading Wheatley’s peer reviewed paper on his study for Ireland “Quantifying CO2 savings from wind power”: or the free pre-submission version here: .

You may also find the Sustainability Energy Authority of Ireland (SEAI) modelling study, which was done in response to Wheatley’s study, of interest. You can download it from here:

Perhaps I can summarise some relevant policy points of my own

I don’t regard your points as policy relevant. What do you believe is the abatement effectiveness in each year (not average for 5 years); please provide links so your figures can be reproduced. It is the abatement effectiveness that is policy relevant because that’s what we need to understand so the errors in the estimates of CO2 abatement cost can be corrected. See the chart here:


I have to agree with Peter Lang.

I also think it is unhelpfull in these discussions to use examples from areas that are only part of a Grid. In the graph of SA , I notice in the graph the Interconnector.

When is the Interconnector used?

I am guessing, but I think it is at times of Peak Demand.

There is no Interconnector for the Australian Grid. It runs from north of Cairns to West of Adelaide.
In terms of Grid management and whole of Australia solutions it is generally of little interest to me what is going on in Denmark, Portugal or Scotland because for a start they all represent a very small part of a very big grid.
Examining Ireland on the other hand is useful because it is an island nation like Australia. The management of the Irish grid can give Australia an insight into how to manage VRE’s to ensure grid stability, etc


Some commenters have been querying moderation rules.
Please avoid posts that are convoluted, irrelevant (Off Topic -there is a separate thread for these) repetitious or circular.
Do not offer as fact what are simply opinions about complex matters.To avoid this provide scientific data, links, refs to support your arguments.
Remain civil throughout. Rudeness will not be tolerated.
Thank you.


Two typos in my previous comment:

Opening sentence after first quote should read: “I accept Wheatley may have used incorrect capacity factors …”

This paragraph was intended to be a quote:

And you repeat Wheatley’s claim that wind is only 78% effective at reducing emissions. A claim which is based on 5 minute correlation analysis suggesting wind displaces 5 times more gas than coal. This claim looks highly dubious after looking at South Australia’s generation since 2005, which indicates wind has displaced much more coal than gas in that state.


Dos 74
Thanks for that information.
As the newer wind farms have better technology (i.e lower Su – higher CF) then the average CF will increase. So in 7-10 years if we have 7 GW wind @ average 37% then generation is more than 22TW.hrs per year which knocks out another $5-6b from the required investment for 95-98% carbon free electricity


David Osmond,

Thanks for your various comments above, very informative.

You’re right about capacity factor discrepancies. I counted capacities for all wind farms listed as registered participants in the AEMO Registration and Exemption list. This includes Codrington, Hepburn, Toora, Windy Hill & Wonthaggi. However, as you point out, these are not reporting data, so I should remove them from capacity calculation.

The Registration & Exemption list gives the DUID (Dispatch Unit Identifier) by which the generator is identified in the SCADA files. But it is incomplete and does not give a DUID for several wind farms. I managed to find them in the data, all except for Portland wind farm, which I have now found with the DUID PORTWF. Portland energy is not included in the data, so I need to add that in.

Note that there were other problems with the AEMO data – I mentioned in the article many double entries from wind farm energy records that I found at a late stage and had to detect and filter out.

When I make these adjustments there will be a modest increase to the capacity factor that will probably align with the value you calculated. I’ll ask Barry to update the article when I do that.


David Osborn,

You have an afternoon bias in your definition in solar hours of 10am to 4pm.

Yes, but I did play around with the the bounds of the solar period and found the calculated capacities were quite insensitive to the the exact hours chosen. Here is the plot redone for the periods you suggest:

There’s essentially no difference between these plots, and the 10am-4pm plot in the article, and the conclusions drawn therefrom remain the same.

This incidentally is partly why I think the anti correlation between wind and solar due to weather is probably weak – if the day/night capacity factor calculation is robust towards moving the solar window around by many hours, the less profound influence of weather is also unlikely to shift the weight of the pattern significantly.


As I am associated with the electricity industry in South East Qld I am aware that the impact of solar PV on this section of the grid has been to move peak demand from (4pm -6pm) to (6pm – 8pm).


Hi John Morgan, just a few more comments about the diurnal analysis of wind. For the 1 year of data corresponding to the 1 year you used, I have wind being ~4% less productive than average during the middle of the day during the ‘solar hours’. I agree there is not a great deal of difference if you shift the solar hours around by an hour or so, so apologies for sending you off on that wild goose chase. Using 5 years of data (from Jan 2010 to Jan 2015), I get wind being about 5% less productive during the middle of the day.

Obviously solar is massively more productive during the solar hours, perhaps ~300-400% more productive than the 24 hour average.

Meanwhile, electricity demand during the solar hours is about 5% more than the 24 hour average.

What I am getting to, in a very round-about way, is that demand is lower during the night than during the day. We don’t necessarily want wind to be completely anti-correlated with solar, producing primarily at night and little during the day. Obviously we want the combination to add up to something that closely resembles demand. That may mean that wind produces only a fraction more during the night than during the day, which is what we are seeing.

Having said all that, I am a firm believer that battery storage will take off in the next decade, and in the next couple of decades the NEM will have of order 100 GWh of battery storage which will help us to match supply and demand over the course of a day.

However matching supply to demand on a daily, weekly or seasonal basis will be much more challenging if we rely on a high penetration of wind and solar. So when analysing correlations between wind and solar, I think it will become more important to do this on these longer timescales, rather than on hourly timescales.


Dave Osmond,

Battery storage is an order of magnitude more expensive than pumped hydro and pumped hydro is not viable at current prices. So I see little chance that the optimistic claims about battery storage are likely to become a reality. Furthermore, 100 MWh storage can have negligible impact on making wind and solar a viable alternative to dispatchable power supplies – which is what is needed.

There are interesting links on energy storage here:
Energy Matters The Renewables Future – A Summary of Findings


Peter Lang, I apologise, I missed your reply to me yesterday morning, and did not read it before I replied in the evening. Never-the-less, I feel that you do not seem to understand my criticism of the Wheatley paper. In Table 2.2, Wheatley indicates than 1 MWh of wind in SA displaces just 0.06 MWh of brown coal in SA, but 0.320 MWh of gas. However we know that coal generation in SA has reduced rapidly in the last decade, as wind generation has rapidly increased, and gas has had very little trend. Indeed coal generation is due to cease completely early next year and the owner of the coal generators blamed the rise of renewables in part for the decision to close the power stations. In light of this, how can the Wheatley figures that suggest wind in SA has displaced a negligible amount of coal in SA be considered credible?

Wheatley obtained his figures by using 5 minute correlation analysis. However this analysis completely misses any longer-term decision making by the owners of generators, or indeed any other long-term trends.

Please let me try an analogy. I suspect there is a very poor correlation between 5 minute demand in Victoria, and 5 minute brown coal generation. The brown coal generators often produce at a near constant level regardless of demand. However we cannot use this correlation analysis to deduce that brown coal generation does not significantly contribute to meeting demand in Victoria. However this is similar to the logic leap that Wheatley uses to determine that wind generation in SA displaces very little coal generation in SA.

Let me also try a thought experiment. Let us suppose that next year we build a nuclear plant in SA. A 520 MW nuclear plant running at 90% capacity factor would generate 4.1 TWh of power in SA, matching almost exactly the contribution from wind in 2014 according to Wheatley.

This nuclear is most likely to primarily displace the high marginal cost SA gas generation, namely from Osborne & Pelican Pt, and probably also some from Torrens A & B. These have an average emission intensity of about 0.6 tC02-e per MWh. If demand on the NEM remains similar to what it was in 2014, then this nuclear plant, producing approximately 2.1% of the 194 TWh NEM generation, would have saved approximately 1.4% of NEM CO2-e emissions. According to the definition in the Wheatley paper, nuclear is therefore 69% effective. Wind at 78% is suddenly looking not so bad in comparison.


Dave Osmond,

Thank you for your reply. I do understand your criticism and I’ve understood it each time you posted it. I replied each time and explained that I believe your criticism is invalid. I’d respond that you do not seem to understand the meaning of CO2 abatement effectiveness and its relevance for estimating the CO2 abatement cost of fluctuating-output, intermittent generators.

If you want to see the trend of how CO2 abatement effectiveness changes over time you need to calculate it for each year and chart CO2 abatement effectiveness of wind generation against time, similar to the chart you’ve posted of generation by technology/fuel type in South Australia.

You also seem to not understand that we have to analyse the emissions avoided by wind across the whole NEM, not just in South Australia.

The Wheatley analysis is an analysis of empirical data. We have to go where the numbers take us. If there are errors in the analysis method or input data we should certainly try to find them and report them to Wheatley. However, I suggest the criticisms you’ve raised so far about 5-minute data versus multi-year trends are invalid criticisms of his analysis, the results and the very important policy implications of those results.

I’ll leave aside discussion of your thought experiments. The Wheatley analysis is of empirical data. Thought experiments should be tested using dispatch models such as used by SEAI in their analysis of emissions avoided by wind in all of Ireland grid for year 2012.
(I’ve provided links in previous comments),


Thanks kindly John Morgan for responding for my comments, and for taking the time to look at other solar-hours definitions.

Regarding your comment that the anti-correlation between solar and wind is weak, it should be pointed out that even a zero correlation is still a good result. Obviously wind is positively correlated with other wind, and solar positively correlated with other solar. However if there is no correlation between wind and solar, then the chance of a few days of very poor solar resource coinciding with a few days of very poor wind resource is greatly reduced.
And as I’ve posted elsewhere, wind does tend to be more productive during winter than summer, which is very helpful.


I would like to clarify a few issues.

The key policy-relevant issue is: what is the CO2 abatement cost with wind generation and how does it change as wind energy penetration increases?

Many analyses show that CO2 abatement effectiveness decreases as wind energy penetration increases. I’ve provided links to Wheatley’s empirical studies of Republic of Ireland and of NEM, SEAI’s modelling study for all of Ireland grid (for a different year than Wheatley’s study), and mentioned Kaffine’s empirical study of ERCOT and Inhaber’s analysis of many earlier peer reviewed studies (and mentioned his curve is too low).

Wheatley’s figure of 78% CO2 abatement effectiveness of wind power generation in the NEM in 2014, when wind energy penetration was 4.5%, is the best figure we have. Nothing said in the comments on this thread has given any valid reason to doubt the 78% figure.

Dave Osmond has said that the capacity factors stated in Wheatley’s report understate the true capacity factors because they overstate the average installed capacity of wind power in 2014. This criticism may be correct and I am waiting for David Osmond to provide data and sources so the capacity factors can be recalculated and corrected if they are wrong.

It is important to note however, the state average capacity factors play no part in the calculation of CO2 emissions saved by wind generation or in the calculation of CO2 abatement effectiveness. Therefore¸ any changes to the state average capacity factors will not change the 78% CO2 abatement effectiveness figure nor will they change the corrections needed to CO2 abatement cost estimates (which are significantly understated). [The only capacity factor relevant in the calculation of emissions avoided is the capacity factors of the thermal generators that cycle and ramp in response to changing wind power output – see equation 3.2, p21 ).

This chart shows the relationship between CO2 abatement effectiveness and the correction required to estimates of CO2 abatement cost if the estimates were based on the assumption that wind power generation abates the grid average emissions intensity.


One last point, the CO2-e abatement effectiveness in the NEM in 2014 would be 75% (instead of 78%) if it was calculated on the same basis as is used in the EU and USA. The Australian estimate is based on emissions intensities using both combustion CO2-e emissions (Category 1) and fugitive CO2-e emissions (Category 3), whereas in EU and USA the calculation is done using combustion emissions only.

I’d also like to add that I greatly appreciate Dave Osmond’s critique. CO2 abatement effectiveness is very important and very few people have an appreciation of how important it is for estimating CO2 abatement cost. As a result, CO2 abatement cost is being significantly understated in most if not all estimates. It is important to get those who do the estimates to understand this concept. However, it is important that the numbers presented in analyses such as Wheatley’s are correct. Therefore, critiques like Dave Osmond has contributed on this thread are very valuable. I’ve appreciated the exchange on this important policy relevant issue.

I’d also thank John Morgan again for the post and BNC for facilitating such discussions.


“The chance … is greatly reduced”. Occasional probability eventually becomes near-certainty of zero-zero power. If we dont want every near-record cold snap to take out a near-record harvest of our frail citizens, the entire capacity would have to be duplicated in despatchable power – probably all OCGT (gas).


Roger, I certainly agree that there is a strong possibility that there will be days of the year with simultaneous low wind and low solar. So this will require substantial back-up. Bear in mind the NEM currently has ~11 GW of gas generation, about half of which is OCGT, plus another ~8 GW of hydro.

So the NEM already has a fair bit of potentially useful back-up for a high penetration renewable grid.

However if we sensibly combine wind and solar, their lack of correlation, or perhaps small negative correlation will reduce the amount of time that this back-up is required, compared to a wind-only or solar-only scenario.

Obviously it would be nice to reduce the required capacity of back-up generation. But reducing the amount it is used is certainly a worthy achievement,


Of that 5 or 6 GW of OCGT in the Oz grid, much of that rapid-despatchability is already committed. Around where I live (off the NEM), crushing plants at mines throw 10 MW of demand on and off. When the OCGTs are winding up to back up the sudden demand, they are not available to back up a sudden loss of supply.

Any spare capacity in Oz’s OCGT fleet will eventually run out as already committed. At some point in the growth of wind-and-solar, stability of the grid will require a matching growth of OCGT. Renewables require us to continue to use and emit fossil carbon, when we should be zeroising our emissions.


Dave Osmond,

I get the impression your advocacy for wind and solar is putting the cart before the horse. You seem to have a chosen solution “wind and solar” and are trying to find any arguments you can to justify them being the needed solution.

But why take that approach. Why not start with the requirements of the electricity system and then, without prejudice, compare options for meeting the objectives at least cost. When you do this, if one of the requirements is to greatly reduce the CO2-e emissions intensity of electricity (e.g. to about equivalent to France’s), then around 20 GW of nuclear plus gas and hydro is the least cost way to deliver the requirements. See main requirements in previous comment on this thread:


Peter Lang

I agree with your approach but based on the market results around the world in the last year or so it is unlikely that nuclear would get to 20GW. Even the CEO of Southern Co. which is building the Vogtle plants in the US will not admit to any desire to build more nuclear even with GHG abatement credits

Existing hydro and gas is probably not enough in a drought year and 20GW nuclear is far too much in mild nights or at least half the weekends so the capacity factor of the nuclear will be in the order of 60-70% and we will need another 4-6GW of Gas or nuclear for peak drought demand, if it is gas, emission targets are weakened and if it is nuclear the capacity factor is down and cost per is up.


Peter Farley

based on the market results around the world in the last year or so it is unlikely that nuclear would get to 20GW. Even the CEO of Southern Co. which is building the Vogtle plants in the US will not admit to any desire to build more nuclear even with GHG abatement credits:

Existing hydro and gas is probably not enough in a drought year and 20GW nuclear is far too much in mild nights or at least half the weekends so the capacity factor of the nuclear will be in the order of 60-70% and we will need another 4-6GW of Gas or nuclear for peak drought demand, if it is gas, emission targets are weakened and if it is nuclear the capacity factor is down and cost per is up.

Peter Farley,

There are many points you’ve raised in previous comments that I’ve refuted but you didn’t acknowledge so we could bring them to closure. So, there is little point raising more points until they’ve been brought to closure.

I’ll make some quick responses to your latest comment:

it is unlikely that nuclear would get to 20GW

That comment is baseless because you don’t state the time frame you are referring to. If we want to cut GHG emissions it is inevitable we’ll have to convert our electricity system to largely nuclear. Renewables cannot make much of a contribution. We’ve had that out on other threads. Hydro can make only limited additional contribution, so best to assume we stick with what we’ve got. France commissioned most of its nuclear capacity over about 20 years; we could too if we wanted to after about 10 years lead time to first reactor in service – i.e. about the same as UAE is scheduled to take from first deciding to go nuclear (in 2007) to first reactor scheduled to be in service by 2017, and fourth by 2020 (they are running on schedule). So, we could have 20 GW in operation in under 40 years from now if we wanted to.

Existing hydro and gas is probably not enough in a drought year

I said nothing about “existing gas”. In fact in a previous reply to you on this thread I said about 20 GW of gas. Refer back to the comment here:

and “drought year” is irrelevant because hydro storage lasts us through decades of low rainfall years. I am not suggesting more hydro capacity be built because it is not economically viable at the moment and potentially viable sites are limited in Australia. Its share will shrink over time.

The rest of the last paragraph is incorrect – see this:


Dave Osborne,

I hope you now understand that the national annual average wind CF in Australia average around 30%-37%

No, I don’t accept those numbers. Until I see evidence to the contrary, I accept the numbers in Wheatley’s report. I’d need to see the data to support your figures and links to the sources so I can check for myself and so Wheatley can reproduce them. I’d also need to know the calculation has been done correctly, not confusing availability with capacity which should be from the commissioned date. At the moment I have more confidence in Wheatley’s analysis than yours since you cannot produce the evidence to support your nimbers. However, as I’ve already explained, the state-average capacity factors are not relevant to the calculation of CO2 emissions avoided by wind generation or the CO2 abatement effectiveness. So the argument about a couple of percentage points is down-in-the-weeds distraction from what is relevant.

I believe Wheatley’s paper is fatally flawed in calculating the current effectiveness of wind on the NEM. Long-term South Australia data clearly shows that wind has displaced far more coal generation in SA than gas generation, in clear contradiction to Wheatley’s paper.

You’ve repeated that four times now, and each time I’ve explained that you do not understand what “CO2 abatement effectiveness” means. The long term trend you are referring to is irrelevant for calculating the CO2 abatement effectiveness. I am wondering if you’ve read my replies to you where I explained this? I’d urge you to read the links I provided so you can get to understand what this is all about. At the moment you clearly do not understand it.


Peter Lang,

I have previously provided evidence that Wheatley did not use the average installed capacity for wind during 2014. I will make another attempt to do so now. But to begin with, you say that we should only be using wind farm capacity which should be from the commissioned date. If everyone did this, then I would not be having these arguments. Wind farm commisioning dates are when the wind farm is complete. However wind farms start generating well before the commisioning dates, as they like to get revenue as soon as possible, as soon as any turbines can be connected to the grid. AEMO publish this pre-commisioning data, and it is because people are using this pre-commisioning data to calculate CFs that they are getting these low CFs. However it is difficult to find the commissioning dates, so it is understandable that people just use all the data without working out if it is pre-commissioned or not. Even I don’t bother, however I do make the effort to estimate the installed capacity for each month prior to commissioning. However for the purposes of the rest of this email, I will not make these pre-commissioning adjustments.

Now getting back to the installed capacity used by Wheatley. He says he used 34 wind farms with an installed capacity of 3394 MW, which you have said that he claims is the average installed capacity for 2014.

The AEMO registered generator list (link at end of post) has 40 or 41 wind farms listed with 3667 MW of registered capacity. BOCORWF1 is listed twice, with 2 different installed capacities (the correct value is the sum of the two values, 113MW). Confusion about the number wind farms relates to if you count Boco rock once or twice.

AEMO does not provide data for 5 of the listed wind farms, Codrington, Hepburn, Toora, Windy Hill & Wonthaggi. John Morgan agrees with me on this point, and is also why the website does not list their data. Weatley also mentions “Note that some smaller non-scheduled generation is omitted from the SCADA dataset”, which is no doubt refering to these wind farms.

These 5 wind farms total 67 MW, so we are now down to 35 or 36 wind farms, and 3600 MW total capacity.

Bald Hill wind farm first connected to the grid around midnight on Jan 29, 2015. For evidence of this, download the AEMO PUBLIC DAILY SCADA file from AEMO for Jan 2015 from the link below, then open the Jan 28-29 file. Search for “BALD”. You will see an entry for BALDHWF on 29/1/2015 at 0:00. There is no data prior to this time or date.

Bald Hill is 107 MW. Thus we are down to 34/35 wind farms with 3493 MW registered capacity as of Jan 28, 2015

Taralga WF (TARALGA1) first connected to the grid on 11/12/2014. Again, this can be verified by downloading the PUBLIC_DAILY file from AEMO for Dec 10-11. It first appears at 11/12/2014 at 0:05.

Taralga is also 107 MW, so we are now down to 33/34 wind farms with 3386 MW of registered capacity as of 10/12/2015

Boco Rock (BOCORWF1) is 113MW, and AEMO files indicate that it first generated on 29/8/2014. I could continue further back in 2014, but that is not necessary to make my point.

Thus, to summarise the timeline of installed capacities:

Date, Registered Capacity, # of Wind Farms
28/8/14, 3273 MW, 32 or 33
10/12/15 3386 MW, 33 or 34
28/1/2015 3493 MW, 34 or 35

Note that these figures include the full installed capacity for the wind farms connected to the grid. It does not include any downward revision estimates for pre-commissioning installed capacities.

It is clear that Wheatley’s figure of 3394 MW is not the 2014 average. His CF values are wrong and too low


Hi Tony, your point is very valid. If wind is generating more than we need, then it is very easy to curtail the wind farm output. Obviously it affects the LCOE if this wind goes to waste, so hopefully we wouldn’t have to do it too often.

Fortunately it is not too often that wind across the country is all producing simultaneously. Moreover, hopefully we will be able to use existing pumped hydro storage or other future storage devices to take some of the excess.


The example I quoted is purely hypothetical.
But it is meant to show what can happen when people start advocating large percentages like 50 percent for generation from renewables. In Australia, renewables effectively means VRE’s.
Any significant hydro is very limited near our population centres. Some of the more senior contributors may remember the Franklin Gorge in Tasmania. Whilst not a hydro project, purely water supply, the Traveston Dam project in South East Qld was extremely politically unpopular and failed to start.
One of the other factors that gets very little attention is transmission line losses. Whilst certain section of the Grid do not have to consider these losses overmuch. In Qld, NSW and WA they are a significant factor.

John Morgan’s maps show significant wind resources near the tip of Cape York. I have tried to find figures on transmission line losses but have not been able to do so. The distances and the quantity of power which is transmitted makes the Australian grid unique. I doubt that resources like Cape York offer any economic opportunities for the Australian Grid.


‘In Australia, renewables effectively means VRE’s’

This prevailing ignorance of the potential for biomass to provide significant electricity is a testament to over a decade of lobbying against development of electricity from biomass by the Greens on federal and state policy formation. We are so far behind other OECD countries in this as well as BRIC countries in our development of this most readily available renewable energy source it is a national embarrassment.

So at present we have 800 MW of installed capacity that is mostly capable of high CFs in the order of 80% plus. This equates to around 3000 MW of installed solar capacity on a CF basis or about 1800 MW of wind capacity. It is a fact that we are not seeing this production from biomass in the AEMO figures as much of it is used by the industries where it is generated – the sugar mills, Australian Paper, Visy, etc. These also use the vlauable co-product of heat and this use displaces use of natural gas or other fossil fuels.

A recent report by the CEFC identified in the short term this could be bio-electricity generating capacity could be doubled to 1600 MW capacity. Other reports by Bioenergy Australia, CSIRO and RIRDC give estimates of 17% to as high as 30% of present electricity base needs (so about 3000 to 6000 MW) coming from available and unutilised biomass or biomass sources that could be stimulated as a result of integrated farming systems.


My apologies Andrew for forgetting about Bio-Mass. I am sure that it has a role to play in future energy and environmental solutions. As you have acknowledged it can not provide 100% of our future energy needs.
Unfortunately I find the Windies and solar PV proponents believe that their favorite is the solution when the scientific facts say otherwise.


Not sure that you fully understood my point. When wind generation exceeds the systems ability to use it the Capacity factor of wind is reduced. So there is an optimal point for wind generation beyond which the capacity factor is reduced and the cost of wind generation per kw as a consequence will keep increasing.


Tony Carden,

You are correct. The quantities escalate rapidly as wind penetration increases. There is a good explanation of the effects in this very interesting analysis: “The difficulties of powering the modern world with renewables
“Figure 3: UK electricity demand and wind generation with wind supplying 50% of demand, February 2013”


Peter Lang, I certainly can’t deny that I am pro-renewables. However I am also open to nuclear. There are many countries in the world that will struggle to go mostly renewable, and for their sake I hope nuclear proves to be a worthy option.

However I don’t believe Australia is one of those countries. We have so much plentiful & economical renewable potential. However, if 3 things happen then I will likely join you in barracking for nuclear.

if China starts to roll out nuclear generation economically, timely and safely at a more rapid rate than it rolls out wind and solar (in terms of delivered GWh/y). If any country is able to roll out nuclear quickly and economically, then it is China. If they can’t, then I don’t fancy our chances.
if a Western democracy follows in China’s path, and also rolls out nuclear economically, timely and safely. And by economically, I mean at a rate that is competitive with wind and solar prices in Australia. And for this point, I mean a current or future example. Evidence from last century will not persuade me, there seems to be too many examples of over-time and over-budget nuclear at the moment that I wonder if a democracy can repeat what was achieved a few decades ago.
if I can see compelling evidence that Australia will struggle to gain a large majority of its electricity from renewables.


I have just posted a comment in Open Thread 23 about Nuclear power development in China. It would be worth your while to have a look. In short, they will have 20GW built by smoko.


Peter Lang, let’s go through Wheatley’s process point by point so we can work out exactly where our disagreement lies.

Abatement effectiveness. I don’t think we have any disagreement on this point. I agree with your statement above “It is “ratio of % CO2 emissions savings to % wind power generation”.
How do you calculate the CO2 savings? Model CO2 emissions with and without wind, and calculate the difference.
How do you model the ‘no wind’ scenario? Which generators would have picked up the slack if there was no wind? It seems to me this is where our disagreement lies. As I understand it, Wheatley uses regression analysis on the 5 minute data to work this out. This is where I believe his error lies. Please correct me if you believe me to be wrong on this point.


Dave Osborne,

I’ll try another approach to explain why the chart you posted says nothing about CO2 emissions avoided or CO2 abatement effectiveness. I expect you believe that the wind bars on the chart represent the proportion of emissions saved. They don’t! Unless you know the CO2 abatement effectiveness of wind power generation you cannot convert the proportion of wind generation to the CO2 emissions avoided. The chart you posted is not about wind’s effectiveness; it’s about the Renewable Energy Targets effect on the proportion of generation from renewables, at least the ones picked out for special favouratism. The RET is a very bad policy, IMO. It is an example of government ‘command and control’ intervention that distorts the market. The first objective of the legislation is to impose more renewables, not to reduce CO2 emissions.

(a) to encourage the additional generation of electricity from renewable sources

If South Australia was an isolated grid, so that other states were not backing up for wind power variability, South Australia’s CO2 abatement from wind farms, at 27% penetration, would be in the order of $100/tonne – refer Submission 259, p3.

In Comparison, the RET Review summarised estimates of the abatement cost of the Large Scale Renewable Energy Target (LRET)3 at $32-$70/t CO2. These estimates, however, are likely underestimated as the analyses do not appear to take effectiveness into account, or at least not fully. If the economic analyses do not take effectiveness into account, and if effectiveness decreases to 53% by 2020, the estimates of abatement cost would nearly double to $60-$136/t CO2 with effectiveness included.

To put these abatement costs in context, the ‘carbon’ tax was $24.15/t CO2 when it was rejected by the voters at the 2013 Federal election. The current price of EU ETS carbon credits and the international carbon credit futures are:
• European Union Allowance (EUA) market price (10/3/2015) = €6.83/tCO2 (A$9.50)
• Certified Emissions Reduction (CER) futures to 2020 (9/3/2015) = €0.40/tCO2 (A$0.56)

Therefore, the LRET in 2020 could be 2 to 5 times the carbon tax, which was rejected by the voters in 2013; 6 to14 times the current price of the EUA; and more than 100 times the price of CER futures out to 2020.

Clearly, the RET is a very high cost way to avoid greenhouse gas (GHG) emissions.

The 53% effectiveness mentioned in the quote is from Wheatley’s study for Ireland at 17% wind energy penetration. For South Australia at 27% wind energy penetration, a fairly similar mix of technology fuel types as Ireland, and assuming South Australia is an isolated grid, the CO2 abatement effectiveness would be around 40% to 45%. At 40%, the CO2 abatement cost would be around $80-$175/tonne. That’s three to seven times the ‘carbon tax’ that was rejected by voters at the last election.

I hope you can appreciate why CO2 abatement effectiveness is such an important, policy-relevant concept to understand.


There are many countries in the world that will struggle to go mostly renewable

No large industrial economy can go mostly non-hydro renewables. This has been explained over and over again on BNC and also in the posts I linked here: . There’s no point in trying to repeat all that here.


Dave Osborne,

Thank you for going to the trouble of extracting this data.

Unfortunately I could not send it to Wheatley in the form it is in. It is unclear to me and I expect would be unclear to him too. I don’t understand what you believe the average capacity factor should be nor where to get the data to reproduce it, so clearly it would be confusing and unpersuasive to Wheatley too. He extracted the data from AEMO and it would have to be shown what the correct average capacity factors are for each state and why his are wrong. I’d suggest the presentation of the data should clearly lay out the capacity by state at the start and end of 2014 and say the dates when capacity was added during the year (by state).

Furthermore, since the state average capacity factors are irrelevant for calculating the CO2-e emissions avoided and the CO2-e abatement effectiveness, I am reluctant to raise this issue with him unless it is absolutely clear – and important.

I suggest, if you want to you, you could post a comment on his web site here:
“Emissions savingfs from wind power: Australia”


Peter Lang, you wrote “I expect you believe that the wind bars on the chart represent the proportion of emissions saved”. You expect wrongly. My plot of the generation sources for South Australian electricity were not to demonstrate wind’s abatement effectiveness. They were to demonstrate the fatal flaw of Wheatley’s paper. That is that each MWh of wind in SA displaces only 0.06 MWh of coal generation in SA, but 0.32 MWh of gas generation in SA and 0.63 MWh of imports.


Dave Osborne,

That’s not a fatal flaw. It’s not a flaw at all. It’s irrelevant. NSW generators are doing a large part of the cycling and ramping to back up for the wind power fluctuation in South Australia. That is, NSW electricity users are paying for the high cost of backing up for South Australia’s wind power.

Your comments demonstrate you haven’t carefully read or haven’t understood the paper. They also suggest you haven’t read the back ground papers I provided links for.

Here’s another example from an earlier comment that clearly demonstrates you haven’t read carefully or haven’t understood this paper and the Wheatley paper of his Irish study.

How do you calculate the CO2 savings? Model CO2 emissions with and without wind, and calculate the difference.

Models are one way. They commonly give too-high values for emissions avoided and for CO2 abatement effectiveness. The other way, which Wheatley’s analysis uses is empirical analysis of historical generation and emissions data. He explains both methods have their benefits and limitations. Modelling is used for projecting and scenario analysis. Empirical analysis gives you the actuals – the ‘truth’ if you like – of what actually occurred. This is important for validating and calibrating the models.

Please read the links I’ve provided in previous comments: Wheatley, 2013; Kaffine et al., 2013; SEAI, 2013.

There is no point discussing this any further until you understand.


Surely the main reason for the transition to non carbon power sources is to reduce GHG emissions.
Real world data shows that intermittent renewable energy generation (like wind) with low capacity factors and requiring backup from fossil fuel generation does not reduce GHG emissions.

For example Germany, which by the end of 2014 had installed;
• 38GW of Solar producing 33TWh (or 6%) of electricity with a capacity factor of 10%.
• 36GW of Wind producing 57TWh (or 10%) of electricity with a capacity factor of 18%.

This intermittent energy infrastructure is backed by gas and a new fleet of load following coal burning power stations to provide power when the sun and wind are unavailable.

The results are:
Germany CO2 emissions from electricity generation are 576 gms/kWh compared to France with 40 gms/kWh.

While German renewable generation has dramatically increased, CO2 emissions from electricity generation are virtually unchanged since 1997 at about 365Mt per year.

German electricity prices are almost twice as high as France.

Unfortunately almost every pledge to COP21 plans to use renewable energy to reduce emissions and if the result is the same as Germany, then emissions BAU will continue for decades to come.


Tom Bond, can you do us a favour and stop using the term ‘energy’ when you are meaning ‘electricity’. In the renewable energy area there are major advances in supply by the renewable energy sources in Europe (and some countries obviously more than others), but overall the contribution of renewable sources of energy is far greater than of ‘energy’ from nuclear reactors (the utilised part of which only consists of the electricity produced, and the vast amounts of heat produced are entirely ‘wasted’. So the energy that is produced from renewables in the EU and many other countries in commitments of various levels at COP 21 are actually fairly meaningful once you stop seeing it all only as being about electricity (which as we all know is only 25-30% of final energy).


For those who think French power generation is cheaper than Germany page 6 of the following document shows that year ahead French wholesale power prices are around E38 vs E33 for France.

Frances oldest current generator was commissioned in 1979 it latest in 2000 i.e 20 years not 10 to reach current capacity These generators supply about 450TW.hrs per year i.e they added 22 TW.hrs per year.
China’s wind generation increased from 45TW.hrs in 2010 to 160TW.hrs last year i.e 28TW.hrs per year. From 2009 to 2014 Nuclear output rose from 97 to 125 or about 6 TWhrs per year.–Nuclear-Power/


Dave Osborne, I’m looking for help with Portland Wind Farm.

I have a DUID of PORTWF which I take to be Portland Wind Farm, reporting in my generation data. PORTWF is not listed in the Reg & Exemption list, so there is no registered capacity figure available. Wikipedia tells me PORTWF has capacity of 195 MW. But, that includes the first stage of YAMBUKWF. So I can’t assign a capacity of 195 MW to PORTWF or I’d be over counting. Also, the peak instantaneous generation for the year from PORTWF was 18.6 MW which seems a bit low for a wind farm of that size.

Do you know what PORTWF represents, how it relates to YAMBUKWF, and what its registered capacity is?


It seems to me that if you want to claim that wind emits CO2 you should also bundle the cost of wind and peak power gas backup but on the other hand also attribute the CO2 abatement effect of wind/peak power plants and silence intermittence argument.

Wind and peak power plants outcompetes high marginal cost electricity generators, which nearly always will be older coal plants that perform below average and thus also use more coal to produce electricity.

The CO2 abatement can therefore in praxis be more than 100% of the CO2 emitted from average coal fired plants because they range between 30% conversion efficiency and 47%. And the peak power plants can also back up all other power generators including nuclear or high efficient coal power plants that thus achieve higher capacity factor.

I full well understand the need for backup for wind but any other electricity generation technology also frequently requires backup. The intermittence of wind and solar is as predictable as weather forecasts. Nuclear and coal power will to the contrary scram every once in a while and especially nuclear will on occasion be out for weeks, months or even years. How much backup does nuclear require?

There has been one post here at BNC that has argued the historic evidence of wind powers CO2 abatement effect.

If you want to calculate the CO2 abatement cost after carefully assessing the CO2 abatement effect then at least in USA there are no other source of new electricity generation that is anyway nearly as cheap as wind power and no electricity generation technology that is cheaper than wind/peak power plants.


Tom Bond said: “Real world data shows that intermittent renewable energy generation (like wind) with low capacity factors and requiring backup from fossil fuel generation does not reduce GHG emissions”

Considering that the backup must be OCGT rather than CCGT, one might add: “requiring backup from fast-responding but inefficient fossil fuel generation”.


Re Germany vs France
1. Correction to my post above German wholesale electricity prices are now 10% lower than France, France’s prices are predicted to rise over the next 10 years and Germany’s are predicted to continue to fall.
2. Germany is building 8GW of new coal but retiring 14GW and there is now an expectation that not all of the 8 GW will be completed

Tom Bond and Roger Clifton.

If anyone was proposing solar or wind as the solution then you are right OC gas is not very efficient.

However If you have a five factor system. Wind, solar, biofuel, hydro and gas, then some proportion of the gas can be CC while fast response hydro and some of the biomass can cover the short term fluctuations leaving CC Gas to run most of the day on high demand days.

While wind and solar are intermittent they are predictable over an hourly timeframe particularly over a wide area so there is plenty of time to ramp other sources.
The addition of some storage or changing the operating regime of the hydro so that is the last used resource allows further optimisation of the CC gas plants because during short term demand dips or early in the demand rise or later as demand is falling the CC plants can be used to recharge storage.

While bulk battery storage is clearly uneconomical, local battery storage at substations can have a very high value in smoothing local fluctuations and avoided grid costs. That is why Energex etc. are installing batteries today. Finally grid control of movable loads such as hot water, pool pumps, many cooling loads etc. can act as very low cost pseudo storage, absorbing excess wind and solar and dropping off when other demands are high.

All of these techniques mean that the contribution of an energy source can, in fact, exceed its capacity factor just as coal does in China. 70% of electricity but a little over 50% CF and nuclear does in France 75%+ of generation, 68% CF


If you have a five factor system. Wind, solar, biofuel, hydro and gas, then some proportion of the gas can be CC while fast response hydro and some of the biomass can cover the short term fluctuations leaving CC Gas to run most of the day on high demand days.

Oh yea, right. “Five factor system” required 2-5 times the capacity and investment to do the same job as nuclear (and don’t forget the many times higher grid costs). You’d need >100 GW of capacity in you “five factor” system as could be done with 20 GW nuclear at 90% CF plus 20 GW gas at about 13% CF to meet NEM demand profile analysed by EDM

You really do need to crunch some numbers instead of continually making wild unsupported assertions.


I am not sure that people read what is posted on these threads.
But further and relevant to this thread.
There is a rule of economics that relates to the overall growth of an industry and that is the law of ever decreasing rates of return.
Put simply wind generation will expand until net returns from wind generation become zero (marginal revenue = marginal cost).

It is obvious to me that there are some contributors to this thread who have a much more intimate knowledge of the Wind Industry than I do so please feel free correct me.

When wind energy sites are proposed, presumably, they are evaluated on the net amount of electricity that will be delivered to the grid.

That calculation must include an estimate of transmission line losses as well as the cost of the transmission line itself. Both are directly related to the length of the transmission line
So if we assume that this is the logical process then the sites that are currently in use already have the best rates of return and the consequent highest capacity factors.

Consequently it is not logical that just because the existing capacity factor for wind is 33.3% that as we add additional wind generation that this capacity factor will remain the same.

Capacity factor will inevitably go into decline and continue to decline.

( I have decided to use this figure 33.3% for simplicity irrespective of the discussions between dos74 and Peter Lang)


Tony Carden,

Thank you for the good points. I’ll add a few.

Wind power is not economic without subsidies and effectively ‘must-take’ regulations now. All future construction would stop if the subsidies and effective mandating were stopped.

The most obvious subsidy in Australia is for Renewable Energy Certificates. They are priced around $35-$40/MWh. That’s around 1.5 to 2 times the cost of electricity from our existing coal fired power stations that wind is being forced by RET and subsidies to replace. The RET effectively mandates that utilities must buy renewables. If they don’t buy enough, they are fined around $93/MWh for every MWh deficit below what they are required to buy.

You also mentioned grid costs, The grid costs for renewables at 50% penetration are around 50 times higher than for coal and 25 times higher than for nuclear. See approximate grid level system costs (in $.MWh) at 50% penetration

Nuclear 1.8
Coal 0.9
Gas 0.5
Onshore Wind 45.2
Offshore Wind 45.3
Solar PV 74.8

These are my linear projection from the grid level system costs at 10% and 30% penetration summarised by Nicholson and Brook from OECD/NEA, 2012, report System effects in low-carbon electricity systems:

These costs are not charged to the wind energy generated. some increase the wholesale cost of the dispatchable generators and some add to the grid costs and are passed on to consumers in the price of electricity. These amount to another subsidy for wind of around $45/MWh at 50% penetration.


To Tony Carden

You are of course right about the economics. Often the best sites for the technology of the day are used first.

However as many people have pointed out the technology is improving and mast heights are increasing so the US fleet capacity factor has increased from 25.4% in 2005 to 32.7% in 2015. This average includes the old plants.

The 29 newest wind farms have an average capacity factor of 37.8% so the technology improvements have more than compensated for the slightly poorer sites.

Of course this problem applies to any technology. the first canals in the British midlands made their owners an absolute fortune with ROI of 30%+ for decades. The last canals built went broke so no more were built.

Similarly for nuclear plants which rely for their economy on very high utilisation once they exceed minimum grid demand there will be more and more times where they cannot sell all their capacity so the “position” of the next nuclear plant to come onto the grid will be worse than the first. No-one really knows where the nth plant can’t sell enough power to justify its construction falls in the market Peter Lang says it is the 20th GW. I think it is somewhere between 0 and 12-15GW, but I am sure we will all be proved wrong.


To Peter Lang

You seem to have a problem with different rates of technological progress.

The link to the Canadian presentation has France in the low CO2/ Low Cost quadrant and Germany in the high cost High CO2. However as I have pointed out and posted the link twice, German wholesale costs are now significantly lower than France and the cost differential is increasing so France is still keeping CO2 low but moving to the high cost while Germany is low cost and its CO2 is trending (very slowly) down.

Secondly you use inflated costs for wind based on a 2012 paper yet contracts from Canberra to India to Chile and the US and Brazil are cheaper per delivered than anyone is offering for nuclear. This takes into account the differing capacity factors. If nuclear is so attractive why aren’t US power operators planning to build more plants. there are 5 under construction with zero planned after that, yet they are adding a nuclear power plants worth of wind every quarter

Using real capacity factors for current technology at high penetrations you need 2-2.5GW of wind for one GW of nuclear but nuclear is 1.5-3 times the price per MW. Then both technologies need storage or gas backup. Nuclear needs hot spinning reserves because of the unit size of the plants, wind doesn’t need hot spinning reserves but needs more storage.

I will agree that the capital cost of a renewable system today may be 15-30% higher than a nuclear system. however the downward cost trajectory for renewables is much more clearly understood than it is for nuclear. Meanwhile the nuclear proponents completely neglect the fact that O&M for nuclear is around A$30 per MW.hour whereas wind is A$5-10 and solar is even lower

To reach the idea that renewables are much more costly than nuclear there is an unfounded number of 40 times the grid costs to integrate renewables to the grid than nuclear

The proposal is for 20 GW of nuclear when for more than 50% of the time there is not 20GW of demand on the grid and the merit order effect will ensure that existing wind, solar and hydro will get preference to nuclear. It may be possible to link 20GW of Nuclear to the grid but it is not possible to get 85% CF. unless there is 10-15GW of storage built as well so the business case overestimates the sales from nuclear and overestimates the economies of scale for building while not accounting for storage costs and therefore significantly underestimates the cost per of nuclear power,


Comments here are starting to veer off topic. This thread is specifically about wind capacity. If you wish to discuss such topics as nuclear vs wind vs solar, costs pertaining etc you should move to the Open Thread. As BNC does not have the capacity to move comments between threads further OT comments will be deleted. It may pay to keep a copy of your comment so that you can re-post in the correct thread, if asked to do so.
Thank you.


Peter Lang, you seem blind to potential flaws in Wheatley’s empirical analysis. You seem to think that empirical analysis provides the ‘truth’.

You suggested that I clearly didn’t understand Wheatley’s work when I said his analysis modelled the difference between CO2 emissions with or without wind.

Perhaps it is yourself that needs to read and understand his paper more carefully. His Australian paper says “Operational emissions savings can be defined as the difference between the observed emissions and what emissions would be in a no-wind scenario, all else being equal. This quantity can be investigated empirically”.

Wheatley’s empirical method uses regression analysis to determine correlations between wind generators and other generators. Once you have performed the analysis, you then set wind to zero in the relationship, and that gives you a model of what would be happening without wind. You are then able to calculate the differences in CO2 emissions between the two scenarios.

However, if you perform the empirical analysis on 5 minute data, as Wheatley did, then you miss any longer term relationships – such as a decision by the owner of a coal power station to shut down prematurely, in part due to the growing penetration of renewables.

To quote your words, ‘there’s no point discussing this any further till you understand’.


Dave Osborne,

However, if you perform the empirical analysis on 5 minute data, as Wheatley did, then you miss any longer term relationships – such as a decision by the owner of a coal power station to shut down prematurely, in part due to the growing penetration of renewables.

In one of my early comments, I said a good, constructive critique of Wheatley’s paper, and others that use similar methods to estimate emissions avoided by wind power, would be very valuable and most welcome. Unfortunately, none of your various attempts to criticise it are not a valid criticisms. Your critique are not of Wheatley’s analysis or paper at all. You are proposing a different analysis. You are stating what you believe would be a more interesting (from your perspective) analysis of long term trends of wind displacing coal generation. Your analysis is not about emissions avoided by wind or CO2 abatement effectiveness at all. It’s about how effective the RET and other incentives have been at forcing wind power to replace coal power. It’s a different issue altogether.

If we want to know the long term trends in emissions avoided by wind power generation and the CO2 abatement effectiveness, then we need to repeat Wheatley’s analysis for each year, then chart CO2 abatement effectiveness by year, as Kaffine did for ERCOT. When you do that you find that the displacement is due to the changing relative costs of the technologies – after incentives!

You’ve mentioned that 5 minute intervals are not appropriate. You are wrong. This clearly demonstrates you don’t understand the analysis. To determine emissions avoided by wind generation with lowest achievable uncertainty we need to use the shortest period available – not more than 30 minutes and the shorter the interval the better. You haven’t understood that key concept yet. Some argue 1 minute would be best.

Regarding you comment modelling you are really stretching the meaning of model.

I asked you to explain what exactly is the error(s) you think you have identified in Wheatley’s paper? Specifically I asked:

Which number?
In which table or figure?
What do you say is the correct number that should replace what you think is the wrong number?
Why do you say his number is wrong and what is the basis for your calculation of what you think is the correct number?

You haven’t answered those questions. Until you do, I Am unlikely to take any more of your repetitive, unsupported assertions seriously.


Total cost of nuclear based on contracted rather than actual cost of Vogtle is double the recent costs of new wind

Wind does not make a grid.  Wind supplies energy, not capacity.  It does not supply frequency control.  Many wind turbines cannot provide reactive power either.  When you add up all the costs of the things required to actually make a grid work, 100% nuclear is far cheaper than 100% wind.


Peter Lang, recognising a limitation in a report doesn’t in any way demonstrate failure to understand it.

It’s very rare for a single result to provide all the information you need. Short timescale measurements show the instantaneous effects of wind power, but don’t always show the long term trend, particularly when it involves large step changes such as the shutting down of coal fired power stations.

It is disingenuous to attribute wind power’s replacement of coal power to the RET, as the RET itself has no direct effect on whether it’s coal or gas that the wind power is replacing. But more wind power in the system creates economic conditions that favour gas over coal, even though it may not be discernible from a short timescale analysis;


Below a certain minimum capacity factor (CF), wind-backed-by-gas emits more than two-stage gas generation alone.

When supply must be increased (by power P) by gas alone, the gas usage would be
P/Ec , where Ec is the gas-to-power efficiency of CCGT

If that same power were to be generated with wind backed by dedicated OCGT,
the average power generated would be PCF from wind plus P(1-CF) from gas
and the average gas usage would be
P/Eo*(1-CF), where Eo is the gas-to-power efficiency of OCGT.

The gas usage and thus the emissions would be the same in the two scenarios when the two usage terms are equal:
P/Ec = P/Eo*(1-CF)
It follows that the minimum capacity factor to make any reduction of emissions is
CF = 1 – Eo/Ec

The efficiency of gas generation depends very much on the plant, however open cycle is approximately two thirds the efficiency of closed cycle gas plant. In that instance,
CF = 1 – 2/3 = 33%

Below the minimum capacity factor, wind farms induce more emissions than they save. How much available land in reach of the grid achieves wind of this minimum quality?


Am I correct in saying that it is your contention that the minimum acceptable capacity factor for Wind Generation is 33%, because at capacity factors below this OCGT would be more effective at reducing GHG emissions.

Regards Tony Carden


To Engineer Poet.

I agree 100% wind is a silly idea, just as 100% nuclear.

A couple of technical points.
Frequency control is about short term response to spikes/dips. Wind is very good at responding to dips in demand, blades can be feathered in seconds, obviously not so good at spikes unless deliberately running below capacity but that applies to all generators.

While nuclear is more predictable, it is not good for frequency control, even if there is spare capacity, ramp rates are measured in hours not seconds, that is why France has gas, hydro and still uses coal and imports from Germany to cover peaks.

It is true that many older wind turbines cannot supply reactive power but the power converters on many new turbines which will be the vast bulk of any new fleet can supply reactive power even if the turbine is not turning

On nuclear cost, see the latest contract in Argentina, which is by far the cheapest published cost for nuclear in the world

A$21b for 2GW of capacity. With 20% equity @ 12% ROI and 80% debt @ 6%. Lifetime 85% CF and $A30/ O&M, power works out at A$132 per hour. This does not appear to include pre commissioning financing costs. It also does not include the cost of spinning reserves for frequency control or fault backup, decommissioning costs nor grid reinforcement.

This is a thought experiment for Australia.

Assume all existing generation is retired over the next 10 years and completely replaced, while droughts eliminate hydro

If we built a 100% nuclear grid it would need 36-38GW to cover peaks with reserve. However at 195 demand, utilisation would be 58-63%. Using a 20% lower average cost than Argentina’s latest contract, the cost per would be about A$155-175 not including fast response backup or any grid re-inforcement. Canberra is contracting wind at a little over half that figure.

An alternative analysis focussing on the capital cost.
Adding 10% for higher labour and cooling costs in Australia and deducting 25% average learning curve effect i.e. the last unit is half the cost of the first one. The capital cost for the nuclear scenario with 3GW of OC gas is about $320-360b. On a 45 year payback with weighted average cost of capital of 7.5% the annual cost of interest and depreciation is about $26b plus another $6b or so in O&M including the small amount of gas used. i.e an annual total cost of $32b for 195 TW.hrs of power

If we built 55 GW of wind and 35GW of pumped storage, the capital cost would be about $92b and $70b respectively. Using a 20 year life for wind and 70 year life for pumped storage, the annual interest and depreciation charges are $9b and $5.3b respectively and the O&M costs are around 0.8-$1.5b so the total annual cost is $15 to $16b for the same 195 TW.hrs. or about A$80-$90 per which is consistent with or higher than costs being contracted all around the world today

This analysis is biased toward nuclear because
a) Weighted average cost of capital for wind and storage is likely to be lower than for nuclear because of reduced construction risk and shorter “time to light”.and the applicability of the storage element to any generation technology including nuclear
b) higher capacity factors in new wind and a wider spread of wind farms over the NEM will reduce the need for long term storage as well as reducing the optimal number of turbines
c) I have used current costs for wind and storage vs significantly discounted costs for nuclear
d) Because of the effect of discounting on future cash flows, increasing the service life for a wind turbine just from 20 to 25 years has almost double the effect on the lifetime cost than increasing the life of a nuclear power station from 45 to 60 years
e) As operation, maintenance, security and decommissioning are a much larger proportion of nuclear (20-25%) than they are of wind+ storage (<10%) the cost of nuclear will rise over time at about twice the rate of the annual cost rise of wind
f) Once a nuclear plant is ordered you have to hope that the technology won’t be disrupted for 45-50 years by yet another new generation of nuclear, 60%CF wind or whatever. A wind turbine has broken even about 15 years after the project agreement is signed.
h) On premises thermal storage and load shifting is usually much cheaper than pumped storage

In spite of all those concessions to nuclear, a nuclear system in Australia still works out to have an annual cost double that of wind and storage.


Is that really the best nuclear can do, PeterF? China apparently plans to punch reactors out at less than $1.5 billion a pop:

There’s not much to be done in the short term about the labour cost differential (though by 2030 you’d expect a fair bit more automation in this sphere), but surely we can work out a way to piggyback off the Chinese economies of scale?

Also, what was the basis for your estimate of a flat $2 billion per GW for pumped storage?


To engineer poet
Wind does not make a grid nor does nuclear. I posted a long reply which has disappeared,however
a) windfarm electronics from Siemens Vestas and GE are designed to provide reactive power even if the turbine is not running
b) Generators can only help with frequency regulation by ramping rapidly. Ramping down easy for wind up hard. Nuclear is too slow in both directions.

Re cost: newest cheapest contract signed (not delivered) in the world is in Argentina is A$21b for 2GW. That works out in the most optimistic scenario @$132/ Around the world wind is being contracted between A$40 and A$100 per This includes the effects of the lower CF for wind.

A 100% nuclear grid including reserves will have 34-38GW of nuclear with 2-3GW of something else fast. Based on the Argentinian priceless 25% for the learning curve the capital cost is A$320-360b. Depreciation and interest @7.5% weighted average cost of capital and 45 year payback annual cost is $23b/yr O&M about $5b total $28b per annum for 195 TW.hrs

55 GW of new wind and 35 GW of pumped storage at current cost is $162b. Allowing a similar learning rate as for nuclear it is $132b. on the higher figure and 20 year life of wind and 70 on storage gives annual costs of $13.5b plus around $1.1b O&M i.e. <$15b/yr. i.e. a little over half the cost of the nuclear system


Roger Clifton

A class 3 turbine at 6,5m/s and an Su of 5 about where the very latest wind designs are, will average 41% CF A shorter blade turbine with Su 4.3 and wind speed 7m/min will average around 45%.

The NEM covers about 500,000 modern wind farms are spaced about 2.5 units per sq km. Therefore we need 5500 to 6,000 sq km or 1% of the NEM.

Average wind speeds across the NEM at 50m vary from 4.3 to 9.6m. About half the area is over 6m/min the top 10% is above 7m/min. Now new turbines are available with mast heights up to 155m where wind speeds are usually 10-20% higher than @ 80m.

Thus even the 6m/min areas @80m/min can achieve 7m/s + Thus in theory we have about 250,000 sqkm where CF can be above 40% and as I said we need about 5-6,000 sq km so

A CF above 40% is commonly available with current generation turbines
B We have about 50 times as much land as we need for high performance wind system


b) Generators can only help with frequency regulation by ramping rapidly. Ramping down easy for wind up hard. Nuclear is too slow in both directions.

Nuclear has no impediment to simply bypassing steam directly to the condenser, allowing a ramp rate limited only by the thermal stress on the turbine.  It’s just that nobody’s asked for this capability yet.  If you can’t ramp wind up, you have to have something else ABLE and RUNNING to do that instead.  Generally that means a turbine that’s started and burning fossil fuel.  If we had lots of interruptible load we’d use that instead, but aside from pumped storage these things are scarce on the ground.

Re cost: newest cheapest contract signed (not delivered) in the world is in Argentina is A$21b for 2GW.

I had to look up the exchange rate, which is AU$1 = US$0.7174 ATM.  This makes roughly $7200/kW delivered.  What this ultimately costs depends on interest rates and capacity factor.  Amortized at 5% over 20 years I get about 7¢/kWh for the cost of money; O&M will be a few cents more.  This is quite competitive.  Once the plant is paid off it will have another 40-80 years of useful life ahead of it.

Around the world wind is being contracted between A$40 and A$100 per This includes the effects of the lower CF for wind.

“Wind” isn’t delivered firm power.  Wind is closer to fuel, which must be converted to delivered firm power at considerable extra expense.

Working that backwards, AU$40/MWh at a CF of 35% yields revenue of AU$123/kW/year.  Using your implicit cost figure of AU$92B/55 GW (roughly $1670/kW) and 7.5% interest, amortization costs $132/kW/yr.  The only way to make this up is with huge subsidies.  In short, a MASSIVE distortion in the market to force wind into it regardless of usefulness.



Your posts contain many figures and quotes. However, many are irrelevant factoids because they do not compare like with like. Your comments would be more persuasive and readers would be more likely to read the links if they were to recognised authoritative sources.

Your comments would be more persuasive to me if they:

begin by defining the essential requirements of the system (e.g. energy security, reliability of supply and low cost of electricity);
then state the year your cost projections are for;
then compare option on the basis of the total wholesale cost of electricity and CO2-e emissions avoided (from the system);
you may also want to compare the total system resources needed (steel, concrete) etc. and the EROEI (but this is secondary, compare the cost of electricity for the various options that meet requirements first.

If you do this you’ll find the ‘mostly nuclear’ option is much cheaper than a ‘mostly renewables’ option. Here are some examples of such analyses (the first three are for Australia and using Australian Government projected costs (these are what the government uses for policy analysis):

Renewables of Nuclear electricity for Australia – the costs
(Figure 6 for costs, Figure 5 for CO2 emissions intensity, Figure 7 for cost of the transmissions system additional to the existing system)
CSIRO eFuture
Decarbonizing UK Electricity Generation – Five Options That Will Work

The last one listed above does not have costs, but you might learn a lot from it – and get a better understanding of why many of the contributors here are saying that intermittent renewables cannot contribute much – they can provide only a small component of global electricity, let alone global energy, and therefore can make only a small contribution to reducing global GHG emissions.


Tony Carden asked for clarification. Yes, if the ratio of the efficiencies of OCGT and CCGT were 2/3, then a wind farm (backed by OCGT) with a capacity factor less than 33% would be a worse emitter than if it were replaced by CCGT. Other values for the efficiencies would give a different minimum capacity factor.

However, the formula derived above is quite general. It measures the minimum useful capacity factor of any intermittent source (wind, solar, lightning…) in terms of the carbon efficiencies of its backup source compared to the source they replace. The sources can include the various coal generators. Note that the formula is about emissions only if carbon efficiencies are used.

(In the above, two asterisks intended as multiplication signs have vanished, interpreted by the webpage as a command to render the intervening text in italics!)


To Engineer Poet
US O&M costs this year are US$24/MW.
hr,-Operation,-Waste-Disposal-Life-Cycle. This does not include long term waste storage or plant decommissioning.

If plant Vogtle in the US which is owned by an existing nuclear operator has a weighted average cost of capital of around 7% when US long term bond rates are 2/3rds of ours how will anyone finance a nuclear power plant in Australia at 5%. Grid operators are allowed to earn 8-10% on poles and wires. Any financier in their right mind is going to want a substantially higher premium for a long life inflexible asset so a correct weighted cost of capital for Australia is probably well over 10%.

Being optimistic Over 45 years payback the cost of capital and depreciation on an $10.5b investment at 7.5% WACC (very hopefull) is $820m per year At 85%CF that is a cost per of $110 + 24/0.71 = $144/

$40 per for wind includes the capacity factor why are you dividing it by 35%

As I have pointed out on numerous occasions no matter what technology you use you have a choice of low penetration and high capacity factor eg US nuclear 19% and 90%CF or high penetration and lower capacity factor France Nuclear 77% and 68% YTD.

If you try for 100% of anything without massive storage the maximum capacity factor is around 60-65%. In Australia to cover peaks with a 10% reserve you need 35-38GW of generation. With 195 TW.hrs demand the Capacity factor will be around 60% which forces up the cost of the nuclear grid to around $180-$200 per

Dumping steam to ramp down is not cheap you are spending all the costs and generating less power. Unless you are dumping steam all the time you still don’t have a fast ramp up capacity.

If you have pumped hydro for ramp management, fault backup and peak shaving which is what Japan has (in fact 29GW of pumped hydro to support 58GW of Nuclear) then the cost of the pumped hydro has to be added to the cost of nuclear. On the other hand you build a few less nuclear plants so lets say its a wash on costs

In the wind case I added 35 GW of storage and added the finance depreciation and operating cost. That gives a total cost of power of just under $80/ including operation and maintenance of both the wind turbines and the storage. This is based on current costs not future 60% CF wind turbines which will not only be cheaper per generated but reduce storage requirements even further


This does not include long term waste storage or plant decommissioning.

Both are trivial cost per MWh. Waste storage is around $1/MWh and decomissioning is around 0.01/MWh.

See IEA, 2010, Tables 3.7a and 3.7d (at discount rate used in AETA, i.e. 10%), and p43:
“Where no data on decommissioning costs was submitted, the following default values were used:
– Nuclear energy 15% of construction costs;
– All other technologies 5% of construction costs.”

Footnote #8: “In the median case, for nuclear plants, at 5% discount rate, a cost of decommissioning equivalent to 15% of construction costs translates into 0.16 USD/MWh once discounted, representing 0.2% of the total LCOE. At 10%, that cost becomes 0.01 USD/MWh once discounted, and represents around 0.015% of the total LCOE”

WNA, 2014, ‘Decommissioning Nuclear Facilities’ (“0.1 to 0.2 cents/kWh”)


Another Question for John Morgan. Do you know at what point that the electricity produced is metered. I am trying to get some idea of what has been allowed for transmission losses.

Regards Tony Carden.


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