Renewables TCASE

TCASE 10: Not all capacity factors are made equal

As I noted in a recent post, my new goal with TCASE posts is for them to be shorter, more targeted and more regular, with the aim being to break big problems in sustainable energy down into very focused questions (each of the new TCASE posts will be a maximum of 1,000 words — my new self-imposed editorial limit for this series!). Editorially, I like to note that if any regular BNC readers are up for submitting a short TCASE post following this format, please email me and I’ll be happy to discuss your idea. Here’s the first of the new batch.


Capacity factor (CF) is the amount of energy a power station generates over time (usually a year) compared to what it could have produced if it had been running at full power for the whole period. (Please read TCASE 2, Energy Primer, for a fuller explanation). The CF for coal-fired and nuclear power stations averages 85-90%, wind farms ~20-35%, solar farms ~15-40% (the higher figure is for CSP with thermal storage). Gas or hydro can be high or low — depending…

Now, it’s very tempting to use these percentages as though they were directly interchangable, and indeed I’ve found that most journalists and bloggers happily do this (or else ignore CF completely and cite ‘peak’ power as though it were the same thing). It turns out, however, that this is a seriously misleading practice, as I’ll detail over the next few TCASE posts.

Consider this.

The Blowagale wind farm on Roaring Forty Peninsula has 50 of the 2.5 MWe (peak) GE 2.5xl turbines (rotor diameter = 100 m, hub height = 75 – 100 m, cut-in windspeed of 3.5 m/s, peak at 12.5 m/s, cut-out at 25 m/s). Its peak power is therefore 50 x 2.5 = 125 MWe. Over a 3-year period, it has delivered 1,115 GWh of energy to the grid. The peak expectation would have been 125 x 8760 x 3 = 3,285 GWh, so the CF is 1115/3285 = 34%.

The Trex coal-fired power station in Smogsville is a 500 MWe unit that’s been chugging away for the last 30 years. Over the last 3 years, it has produced 11,300 GWh (out of a possible 13,140), for a CF of 86%.

Okay, on an energy-for-energy basis, all we have to do is build 11300/1115 = 10 of the Blowagale-sized wind farms to replace Trex, right? Actually, that’s dead wrong — at least in the real world — for many reasons, which I’ll explore in the next few TCASE posts. Yet, that’s the impression that’s often given by ‘advocates’ (to use a euphemism).

First, let’s briefly consider what has determined these two CFs.

For Blowagale, the following issues are important: (1) how many turbines are operating (not out for maintenance), (2) the amount of time the wind speed is above the cut-in minimum (3.5 m/s) and below the cut-out maximum (25 m/s), (3) choice of generator size per turbine (I’ll explain this in a future TCASE), (4) whether the electricity is bought by the grid, and (5) wind speed and duration when within operating bounds. When the wind is blowing at 6 m/s, for instance, the power per turbine will be ~0.5 MWe, compared to the 2.5 MWe peak output in 12.5 m/s winds (between 12.5 – 25 m/s, the output remains 2.5 MWe, as dictated by the fitted generator and gearing, etc.).

As you can see, the CF of a wind farm is very much hostage to the variable (and uncontrollable) nature of the wind resource. For Trex, things are rather different. I’ll refer to an earlier comment I made (BWB), and an expansion by Gene Preston (GP):


BWB: A key thing to remember is that, in simple terms, capacity factor = availability factory x demand. For coal, nuclear and gas, their availability factor is determined predominantly by scheduled outages, for standard equipment maintenance, refuelling etc. For plants operated in baseload, demand is nearly constant (i.e. that coefficient is close to 1). A capacity factor for nuclear power might be 90% over a year, assuming 1 month out of each year for refuelling and scheduled maintenance. For the other 11 months, its availability factor is closer to 99% — SCRAMs are what takes this below 100%.

Wind is quite different. It’s availability factor is determined by when the wind is blowing, in addition to scheduled maintenance and, for a wind farm of many turbines in total, the occasional failure of an individual turbine. The engineering availability factor might be in the order of 99% for wind too, but the wind ‘fuel’ is quite a different matter. Sometimes it will be blowing strong enough to deliver near 100% of nameplate capacity, other times it will be 50%, or 20% or whatever. Sometimes, when it is becalmed or too windy (such that the turbines are shut off to avoid damage), it will be 0%. On average, over a year, it will be about 35% in good sites. But this power is not ‘dispatchable’ — it cannot be guaranteed (without energy storage), since the wind is fickle.

What the WWS study says is that for a widely geographically dispersed set of wind farms, you can guarantee, to the equivalent of an 85% availability, a ‘capacity credit’ of about 12%. So, in rough terms, the 12% capacity credit for wind is the equivalent of the 85% capacity factor of a coal-fired power station.


GP:  We need to make a distinction about annual peak, weekends, and low load periods of the year. The coal plant reliability is determined mostly by the forced outage rate (FOR), which could be as good as 95% (5% FOR) when the coal plant is needed most, during the peak load periods. Many maintenance problems can be deferred to the weekend when the load is less. This type of problem usually does not greatly affect the reliability. Then scheduled maintenance is scheduled for light load periods of the year when the plant is not needed. When you do a loss of load probability study, you will find that the greatest loss of load is during the peak load periods, not the lighter load periods. A plant failure during the lighter load periods usually has little consequence, provided the network is electrically stable for the loss of the largest generation within a geographic region.

The annual capacity factor is mostly determined by demand for a coal plant. Coal can go into load following frequently and is dispatched after natural gas and before nuclear, which is even more base loaded than coal. Wind generation can cause gas and coal plants to be backed off because wind had a lower incremental energy cost than either gas or coal. Therefore adding more wind to a region will cause the capacity factor of coal to drop a little, especially when the wind runs during light load periods, which is does frequently. However because coal plants are difficult to dispatch they cannot be run back very far to accomodate wind. Because of the unpredictable nature of wind there must be kept on line a certain amount of gas and coal in the event wind is not sufficient. But there is only a certain amount you can swing gas and coal generators. Therefore as more and more wind is added it becomes more difficult to dispatch the total set of generators.

It’s possible to have some stablity problems with the network as wind is swinging from low to high levels. As you keep adding more and more wind you will reach a point where wind has to be dumped even if there are no transmission limitations. This is because the gas and coal generators cannot be swung enough to accomodate all the wind. Therefore wind is going to have an upper limit, probably no more than about 30% of the total energy. The only way to simulate the network to see how it work is in an hourly simulation model. That model can also be a montecarlo model considering random failures of both generators and line and even wind variability. Every once in a while the hourly model will run into difficulties that require dumping load.

This is the only correct way to model the system.


So, if Trex was operating as a full baseload plant, its CF might be as high as 95%. If it was given an intermediate load-following mode, it might be as low as 60 – 70%. They key is, Trex’s CF is flexible and determined by the grid requirements. Blowagale’s CF is fickle, determined by the wind characteristics, and is (mostly) independent of the grid requirements.

That’s enough for now — more on this CF conflation problem in future TCASE posts…

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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.

58 replies on “TCASE 10: Not all capacity factors are made equal”

Barry We appear to measure several things in addition to capacity factor. These would include an index of the ratio of output to demand over time. This would give us a measure of how well renewable electrical output are matches to electrical demands. Renewable advocates argue that consumer electrical use flexibility will cope with rigid renewables output schedules. An measure of potential consumer flexibilities should be developed and applied to our attempt to match output to demand. The point is to answer the question, “does changing consumer behavior provide a real answer to renewable output limitations?”

We also need an index of carbon mitigation effectiveness. This index should answer the question how much does it cost to displace a given unit of CO2 using various proposed forms of mitigation technology. In the case of wind, the question to be answered would be, “How much would it cost to displace a ton of CO2 at a given level of wind penetration.?”


Thanks Charles, the output vs demand would indeed be a useful thing to measure, and something we intend to tackle fairly early on over at Peter Lang and others have already made a good fist at calculating carbon mitigation effectiveness, though I suspect there remains much detail left to be worked through.


The nameplate capacity of a wind turbine is somewhat arbitrary, therefore, so is the capacity factor, because current pre-build estimates are based on wind resource surveys, and calculations made based on nameplate capacity.

For decades now, the capacity factor of wind power measuring the average energy delivered has been assumed in the 35–40% range of the name plate capacity. Yet, the mean realized value actually measured in the field is well below 20%; accordingly cost is a minimum two-thirds higher and the theoretical reduction of carbon emissions is at least 40% less than projected.

For the above I have been very generous toward wind, in an attempt to ward off claims of superior performance by some installations being more typical; in most cases things are much worse. In any other rational engineering field, it would be recognized by now that the model is seriously flawed and efforts made to adjust it to better reflect experience. The fact that in most planning, the twenty-year old models that have been shown to be miserable failures are still being put forward.


I think if Ontario used that factor then they would have to multiply the nameplate cost of wind by 6, in which case even the high estimate (26B) they got from AECL for ACR-1000 nuclear power would have been better.


SCRAM is a foolproof mechanism to quickly shut a reactor down.

A typical reason for a SCRAM is that the automated safety systems detects any out of hundreds of different things that are slightly abnormal and decides to shut the reactor down; like a sensor not responding or reporting erroneous data or one of a set of redundant valves not opening or closing as it should. It can also be activated by the reactor operators under their own judgement.

SCRAM is usually implemented as a set of control rods that are held suspended by a claw-like device that require a continous current to hold the rods. If power is lost to the mechanism for any reason at all the control rods are passively driven into the reactor by gravity.


Clearly several metrics are needed. For wind and solar a c.f. for the mid winter and mid summer month would be revealing. In the case of solar with storage a useful estimate would be the probability of an overcast week. That is ‘natural downtime’ not unplanned design failure. Clearly the makers of the Wollongong wave machine didn’t plan for it to be washed on to rocks. Mechanical failure probability would have to be based on historic records if they exist.

Since new grid generation will be coupled to the existing system perhaps the best question is whether the addition improves the system. That is does the addition outweigh increased use of carbon backup to lower both total emissions and average cost.

I think a handy use for c.f. is estimating ‘adjusted’ capital cost. Suppose onshore wind cost $2.50/w and connected offshore wind cost $4/w. Suppose the respective c.f.’s were 20% and 30%. Then onshore at 2.5/.2 = $12.50 beats offshore 4/.3 = $13.33.


Not all capacity factors are created equal, and there is a very clear set of definitions of the different species of outage in the IEEE Std. 762-2006, “IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity.” (This is from Bill Hannahan, cited on Nuclear Green – thanks, Charles!)

8.13 Net capacity factor (NCF): Equals 100 times net actual generation / the energy that could have been produced by a unit in a given period of time if operated continuously at maximum capacity.
3.22 Planned Outage Factor (POF): The fraction of a given operating period in which a generating unit is not available due to planned outages. Planned outage: The planned outage state is where a unit is unavailable due to inspection, testing, nuclear refueling, or overhaul. A planned outage is scheduled well in advance.
3.26 Unplanned Outage Factor (UOF): The fraction of period a generating unit is not available due to unplanned outages. Unplanned outage: The unplanned outage state is where a unit is unavailable, but is not in the planned outage state. (Unplanned outages are subdivided into maintenance outages and forced outages) Maintenance Outage: A maintenance outage can be deferred beyond the end of the next weekend, but requires that a unit be removed from the available state or another unplanned outage state before the next planned outage.
6.11 Maintenance outage hours (MOH) The phrase maintenance outage hours represents the number of hours a unit was in a maintenance outage state.
3.14 Forced Outage Factor (FOF): The fraction of a given operating period in which a generating unit is not available due to forced outages.
6.10 Forced outage hours (FOH) The phrase forced outage hours represents the number of hours a unit was in a Class 0, Class 1, Class 2, or Class 3 unplanned outage state.
A Class 0 unplanned outage results from the unsuccessful attempt to place the unit in service.
A Class 1 unplanned outage requires immediate removal from the existing state.
A Class 2 unplanned outage does not require immediate removal from the in-service state, but requires removal within 6 h.
A Class 3 unplanned outage can be postponed beyond 6 h, but requires that a unit be removed from the inservice state before the end of the next weekend.

I think adhering to these standard definitions would be a very good idea in any discussion of capacity or reliability. Maybe Barry could post these in Part 2 to give them a home at the top level of the TCASE series.


Thanks Barry and everyone for the CF etc information. Out of all of it [planned and unplanned outages etc etc etc] it comes down finally to the poor bugger who has to manage the load. For wind load manager, it would be a nightmare. Which is how Colin Keay described it in his pamphlet, Gigawatts. Anyone who thinks wind could ever provide base load or peak power is deluding himself unless, in the case of the US, you covered the entire states of Texas and Louisana with wind farms. For three of the four last days,our local wind farm produced zilch power. Here in South Australia we need to insist that our government stops building the confounded things. We’re heading the way of Denmark who have stopped building them. They learnt the hard way.


Has anyone else noticed that the wind apologists have gone from claiming that baseload is not needed, to claiming wind can deliver baseload, provided you redefine baseload the way they want?

The argument has moved from denying the existence of the need, to semantic gymnastics to show it can in fact, cover that need.


I don’t know what I was referencing – it was just something I found. Since they referred to the US ISOs, I thought it might have some meaning – I assume they are told by legislation they have to come up with a number, and it probably isn’t allowed to be too low, so that’s the number. Personally I would have thought it would be less, and so I think did futurepundit, who I think elsewhere came to the conclusion it should not be more than 10%.


From the current entry on wind power in the wikipedia
“According to a 2007 Stanford University study published in the Journal of Applied Meteorology and Climatology, interconnecting ten or more wind farms can allow an average of 33% of the total energy produced to be used as reliable, baseload electric power, as long as minimum criteria are met for wind speed and turbine height.[19][20]

In a 2008 study released by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, the capacity factor achieved by the wind turbine fleet is shown to be increasing as the technology improves. The capacity factor achieved by new wind turbines in 2004 and 2005 reached 36%.[21]”

Futurepundit took the phrase “33% of the total energy produced to be used as reliable, baseload electric power, ” and multiplied it by the capacity factor of about 33% to get

This part talks about a capacity credit of 20%, but doesn’t say how it gets that number.


I guess I never read the post properly, since BWB mentions capacity credit at the end
“a ‘capacity credit’ of about 12%.”
Using the combination of numbers
“33% of the total energy produced”
“The capacity factor achieved by new wind turbines in 2004 and 2005 reached 36%”
which is just about 12%.


Anyway, I think the “capacity credit” should be emphasized when talking about windfarms, more than the “capacity factor”. If nuclear can provide a capacity credit of 85% (I’d guess better than that) and wind only 12%, then wind nameplate is worth only 12/85 of nuclear nameplate = 1/7th. So to compare non-CO2 producing power, you would have to build 7 times as much wind nameplate as nuclear nameplate.
To that you have to add the extra transmission lines.


Of course, that means dumping 2/3 of the power that the windfarms generated. If you don’t want to dump that power, you have to store it somehow.
Do you build CAES? Do you convert air and water to ammonia? If you do, you have to add that cost on as well.
How much does that cost? Does it add or subtract to the energy cost of non-CO2 windfarms? You see I’m not interested in windfarm costs that in any way incorporate fossil fuel backups, because I don’t believe fossil fuels are going to be available, a la David Rutledge, so we need to cost and plan things as if fossil fuels were not available, since I believe that’s the imminent future, not just a desirable future.


Lawrence, on 24 May 2010 at 2.54 — One or two CAES are in planning here in the States. Other alternatives are to use the excess electricity immediately for purposes which do not require on-demand delivery; pumping water and desal come immediately to mind.


Lawrence, @ 24 May 2010 at 1.39:

From the current entry on wind power in the wikipedia
“According to a 2007 Stanford University study published in the Journal of Applied Meteorology and Climatology, interconnecting ten or more wind farms can allow an average of 33% of the total energy produced to be used as reliable, baseload electric power, as long as minimum criteria are met for wind speed and turbine height.[19][20]

Last week 18 wind farms distributed across south eastern Australia demonstrated that this statement is wrong. The 18 wind farms have a total capacity of 1609 MW.

The actual total output and capacity factor for each day were as follows:

Date; MW; CF
17/05/2010; 31; 1.9%
18/05/2010; 19; 1.2%
19/05/2010; 51; 3.1%
20/05/2010; 80; 5.0%
21/05/2010; 168; 10.4%
22/05/2010; 242; 15.0%

The very low capactiy factors from widely spread wind farms demonstrate the fallacy of Mark Diesendorf’s advocacy of “The Baseload Fallacy”, which put simply says “the wind is always blowing somewhere”.

I have a stacked area chart of the output of the 18 wind farms over the past month. It shows very clearly the high correlation of the wind power output from all the wind farms across this region.



The term Capacity Credit is explained here:

The Australian Energy Market Operator (AEMO) allows a Capacity Credit for wind power of 3% in South Australia and 8% in Victoria. (, p68)

However, if Kent Hawkins is anywhere near correct, more gas capacity is needed with wind in the system than without. So from an investment perspective, the capital cost of gas generation capacity would be greater than if there is wind power in the generation mix than if not. The capital cost of the gas generators must be added to the capital cost of the wind farms.

Regarding the comments about energy storage, the recent comments on the Pumped-hydro thread may be of interest. We need in the order of 100 times as much energy storage capacity for intermittent renewables as we would for nuclear to meet our demand for power.

If you are wanting to compare the cost of some options this may help you with methodology, assumptions and some unit costs. I may be able to help or point you to other sources if you need more.


Lawrence, it’s worse than you think. Capacity credit is not a constant – it declines as the penetration of wind power increases, as I’ll detail in a later TCASE post. By comparison, for nuclear in the US, the capacity credit is already >90%, and it will be unaffected the construction of more power stations.


Yes DV8. The wind devotees will say and do anything to convince the people that wind can deliver base load. They are the ultimate in peddling the myths and fictions of wind and the renewables in general. We must expose them for the liars that they are.


Peter Lang: Lightbucket makes the following comment in his excellent piece on capacity credit.

do you know what L might mean here? can we get reliable power from renewables if there is insane overbuild? (if yes, it still won’t be done I reallize)

Looking further ahead, a more elaborate network of renewable power sources can be set up if we have a large enough grid. Between them the various renewables can provide power reliably, even though each renewable individually has a relatively low probability of being available. (That issue is for another blog post though.)


greg meyerson, on 25 May 2010 at 2.25 — Approximate as follows: assume wind farms are equi-size, equipotent and statistically independent in when each can generate. The last assumption is rather unrealistic, but good enough to start with for a purely conceptual model. Now suppose each can generate 25% of the time. That is, each is not capable of generating 75% of the time.

So the probability that two are not generating at the same time is (3.4)(3/4) = 9/16, so at least one is capable of generating 1- 9/16 = 7/16 of the time; that three are not generating at the same time is (9/16)(3/4) = 27/64 so at least one is capable of generating 1-27/64 = 37/64 of the time and so on.

Choose your grid reliabity and determine how many such (statistically independent, remeber) wind farms you need to assure that at least one wind farm is generating. If just over 56% is good enough then 3 statistically independent wind farms suffice. Once settled upon, add up the cost of all the wind farms plus transmission lines and compare with other methods.

The wind farms which are not generating when it would be possible providing what is usually called rotating reserve and the operators are paid something, not much, to proide this reliability service. So one can calculate the total cost paid to the one generating wind farm plus what is paid to those acting as rotating reserve when capable of doing so.

Up until this point, there is little difference between wind and more usual forms of power productiion other than the avaialbility for each wind farm is much lower than for an NPP, say. But worse is to come: statistical independence does not hold for wind. Wind is highly correlated across vast regions and at this point one engages the services of a trained meteorologist to determine such correlations. Then run the statistical argument once again. I suspect, without knowing, that the conclusions will be most unpleasant compared with more usualy methods of power generation wherein statistical independence of outages is a good approximation to reality.


Based on Peter’s figures above, where the base was about 2% of rated capacity, you’d need about 50 times as much windfarm capacity as you hoped to get in practice out of the system. Given this differential, it might make more sense for wind advocates to pitch for offshore wind, because that clearly isn’t 50 times as expensive as onshore wind. You might get out of the deal for about 10 times overbuild.

Then you’d have to build in massive grid storage to harvest the ten times overbuild. The costs would not be pretty though. It’s hard to imagine getting any change our of $AUS20 billion per GW for the wind installation and take your pick on connectivity and storage.


greg meyerson, on 24 May 2010 at 23.23 Said:

peter: the idea seems to be that the more wind you have, the more unstable the system, precisely the contrary of wind advocates.

is this about right?

The answer is an emphatic, Yes!

However, the wind advocates are denying that more wind penetration (ie a higher proportion of wind power in the system) leads to greater instability. They do argue that more wind power ovar a large area reduces the volatility, but that is not the same as reducing the instability.

I forgot to include this link in my previous post. See especially Parts I and V.


Ewen Laver,

Even if we had wind capacity 50 times greater than demand, it would not have generated sufficent power to meet demand on 17 and 18 May. We had a calm period over the whole of SE Australia so that the 18 wind farms had an average capacity factor of 1% on thjose days. More important, there were 16 5-minute periods when there was no generation whatsoever.


thanks everybody: Peter, David, Ewen.

I did know, from reading David Walters on German wind, that the independence assumption underlying the wind argument from geographic dispersion was B.S.

the capacity credit results make this clear empirically. and of course, what Peter Lang just showed us (wind results). I like the distinction between volatility and instability. the latter is more a property of the stress on the “backup” system.

anyone have any comment on lightbucket’s reliability claim, that I quote above?

I can’t imagine a high penetration wind/solar system being built anywhere save places with loads of hydro. and the only reason to do that would be fear of nuclear.


But as you say Peter, what goes for the overbuild on windfarsm is true for the hydro. If you built 50 times over you’d have to be able to store 50 times over for as long as it was at rated capacity.

Just as it is true that all windfarms could be in lull, all windfarms may well be operating at rated capacity and you dare not dump any of that.

So imagine we have built 25GW * 50 of wind ie. 1.25TW then we have to be able to store all of the surplus (1.225TW) for as long as it runs. Let’s say it runs for 6 hours. That’s enough pumped hydro to store 7.35TWh. I’d hate to think what that would cost. Didn’t you quote $2000 per KWh for pumped storage?

Yet that’s only 12 days worth or so. Crazy stuff, and it’s just so stupid that people will focus on quite minor details to suggest that somehow, the whole thing might work.


The plan is to introduce Smart Metering / Smart Grid with a big smile, saying it will be wonderful, allow consumers to see their power consumption in real time. What they don’t tell you, is that after all the Smart Meters are installed, and people are used to them, all consumers will pay Market Price + Surcharge for electricity.

And RPS’ will make Wind 20-30% of Grid Average Generation. So Wind is low, Electricity Price Skyrockets, those consumers who are not so wealthy, will be forced to reduce electricity consumption, because they won’t be able to afford the high power cost.


Ewen Laver,

Yes, and soon we’d have enough wind mills to supply all the world’s energy needs …. if only the wind would blow all the time !!


The U.S. Navy reactor operators have defined SCRAM as “Super Critical Reactivity Abatement Mechanism”, although this is an after-the-fact effort to create a so-called backronym.

In reality, the etymology of the term is lost in the sands of time.


When we are talking greenhouse gas emission factors for say a state, these are worked out using the total greenhouse gas emissions divided by the total electricity sent out via the grid across a year (with some adjustment for interstate electricity transfers.

Noting that there are differing capacity factors for different generation sources, perhaps the most important question is how these combine together in delivering the outcome value.

In South Australia, with more gas fired generation my understanding is adjustments to gas fired outputs can better complement the wind intermittency compared with say Victoria’s system (again noting that there are interconnectors as well)

The key question for me is to understand by how much south Australia’s emissions are reduced in a year from the installed renewables compared with a grid that had no renewables (or what would SA’s grid factor be if we turned off all the wind farms). I don’t believe that the answer is zero and I don’t believe that the renewables totally displace coal and gas powered generation either.

It is easy to point to periods when the availability of wind is very low, and alternatively there are periods when wind is producing most of SA’s off peak demand.

To me, getting accurate assessments of the overall impact on state emissions is the key to understanding the greenhouse displacement value/MWh of renewables in a given grid or region across a year.


greg meyerson, on 25 May 2010 at 12.06 — Here in the PNW we have “loads of hydro” but not enough, anymore, to use just that. So adding wind power around here makes economic sense (until to about 20% of average load) to extend the hydro resource whenever the wind is blowing.

The approximately 20% limit is all that hydro can backup. So that’ll be it when that much wind is eventually installed; it’ll be quite a while.

It is true there is “nuclear adversion” around here; this is the result of the monumental regulatory failure(s) causing WPPS to declare bankruptcy.; only one of the four reactors on which construction was started was actually finished and is running. Well, I think the one electric power reactor at Hanford is one of the WPPS four; not sure as everybody keeps out-of-the-news about it.


Tim Kelly,

Yes to most of what you say. Gas shadows wind power variability better than coal. Shadowing wind requires more gas to be burnt tha if gas was simply following the changes in demand. The increase in gas use when shadowing wind power is significant.

The cost of electrcity is much higher with a mixed wind and gas generations system than with gas alone. But the additional CO2 savings are marginal. The cost of avoiding a tonne of CO2 is much higher with the wind and gas system than with gas alone. See this article, especially the section on Wind, for more explanation:

The short term and long term view give different answers. In the short term, where we are working with the back up generators that are already in place, then the CO2 reductions look more significant than if you take a long term view. Fot the long term view we make investment decisions. If we do not have wind in the system, w’e invest in CCGT to provide baseload power. In Victoria, CCGT would emit about 0.41 t CO2-e /MWh. However, if we ar going to invest in wind power, and need to back up for that, then a significant proportion of the gas muct be OCGT instead of CCGT. OCGT would emit 0.66 t CO2-e /MWh if running at 85% capacity factor. However, shadowing wind, the emissions of combined CCGT and OCGT may be more like 0.6 t CO2-e /MWh.

Importantly, the cost of electricity from CCGT alone would be $55/MWh, but for the mix of Wind, CCGT and OCGT I calculate the cost is about $93/MWh (all figures are from rough calculations).


Tim Kelly,

I forgot to mention cost per tonne CO2 avoided:

Wind, OCGT & CCGT = $50/t CO2-e avoided
CCGT only = $22/t CO2-e avoided


Thank you Charles. I hadn’t seen this before. I noticed you published it arout the same time as Barry posted this: This looks at the avoidance cost for Australia but from a time-phased, technology-mix approach.

The figures I posted above are preliminary figures I’ve calculated for options for replacing Hazelwood Power Station. I am working on it now.


An excellent post, especially all the different kinds of CF. AT a power station, to remind long term BNC folks, we don’t actually use CF in real time. Nor does the ISO, really. The terms used from Nuclear Green are, if memory serves, NERC codes assigned to changes in CF per the CF definition used.

What we care about is “availability”. Availability is what is listed on a per unit scale lit up on many ISO room-wide screens. It’s what can come on line when they want it, and what will *stay* on line when they need it. Wind is off to one side and, at least for now, is measured by actual power produced in MWs. Since it is not reliable…the ISO doesn’t rely on it and thus schedules only a very small amount of it in terms of availability at any given time.

The difference in CF for gas, nuclear, hydro and coal and that of wind and solar (but mostly wind) is that the *quality* of the negative number, that is, the % of name plate capacity that is NOT available compared to that of wind and solar is not the same, even if the numbers were equal, which they are not, nor ever will be. that is because plants regularly come down on a *schedule*. When a plant isn’t producing it’s because they’ve notified the ISO up to one year in advance they are coming out to fix stuff, refuel for nuclear, whatever. It’s that “unplanned” non-CF that is important or unplanned “unavailability” that makes on demand power so much more usable and easier to plant for and cheaper. Wind is NEVER schedule to unavailability. Period.

During one of the video debates noted a few months ago here sponsored by Forbes magazine, the anti-nuke guy stated “you all know that nuclear isn’t available 15% of the time” ((!!!!!)). I almost chocked on my taco I was eating while watching it. ’nuff said.


Thanks for that post, David: especially the material on the “quality” of the negative number.

very important point.


Thanks for your response.

Beyond cost estimates, what I am really determined to see is an accurate annual accounting system that truly captures how much CO2 is actually being avoided in the different parts of Australia from renewables.

For good or bad, we are in an experiment but not one that is being measured properly.

The Federal Government on their Q&A for the National Carbon Offset Standard are advising consumers that “However, GreenPower™ and other renewable energy purchases can be treated as zero emission sources of electricity under the NCOS for the purpose of calculating a carbon footprint for carbon neutrality. For example, if an organisation purchases 100 per cent GreenPower™ for all its electricity requirements, then its carbon footprint will include no emissions from electricity consumption”

My view is that this advice is wrong on so many levels from accounting through to accuracy through to a lack of definition of what actually makes a 100% contribution.

However I would like to move to the measurement of what renewables do achieve in the mixture of grid sources all feeding in at varying rates at varying times.

I wish to understand what the difference is as it actually occurs in each state, because it may mean that investing in renewables in one place has a better greenhouse outcome compared with renewables in another.

As for the cost, many solutions are cheap compared with the financial harm caused by annual emissions if we continue with A1FI behaviour and reduce global GDP by 50% to 90% by the end of the century.


Tim Kelly,

I agree we need to improve our measurement of the actual GHG emissions. I have a few random points in reply to your comments.

Beyond cost estimates, what I am really determined to see is an accurate annual accounting system that truly captures how much CO2 is actually being avoided in the different parts of Australia from renewables.

For good or bad, we are in an experiment but not one that is being measured properly.

Did you see the Kent Hawkins article?
Yesterday, Kent Hawkins posted a four part series on the extra emissions caused by wind generation. The studies are for Colorado, Texas and Netherlands. Here is the link to Part I: These seem to confirm that the calculator is giving roughly the right amounts of extra GHG emisisons from fossil fuel back up for wind generation.

Australia should be able to do a much better study than these to determine the extra emissions caused by back-up for wind generation. We have accurate measurements of power output at 5-minute intervals for every scheduled generator and the larger unscheduled generators. It is all freely available on the AEMO web site. We should be able to get the fuel usage from the fossil fuel generators. We have relatively isolated regions such as Western Australia and South Australia. It would seem to be the world’s best locality to find the real emissions due to shadowing intermittent renewable energy sources.

The Federal Government on their Q&A for the National Carbon Offset Standard are advising consumers that “However, GreenPower™ and other renewable energy purchases can be treated as zero emission sources of electricity under the NCOS for the purpose of calculating a carbon footprint for carbon neutrality. For example, if an organisation purchases 100 per cent GreenPower™ for all its electricity requirements, then its carbon footprint will include no emissions from electricity consumption”

My view is that this advice is wrong on so many levels from accounting through to accuracy through to a lack of definition of what actually makes a 100% contribution.

I agree. In 2007 the Federal Treasurer instructed the ACCC to conduct an investigation into “Misleading claims about carbon offsets” . However, following the change of government in November 2007, the government closed the investigation down. The ACCC had already called and received submissions and the submission period was closed. The submissions wer never made public. The ACCC distributed a whitewash report which said, in effect “you can trust GreenPower”. I presented a submission to that enquiry. The main part of it is now published here:

However I would like to move to the measurement of what renewables do achieve in the mixture of grid sources all feeding in at varying rates at varying times.

I wish to understand what the difference is as it actually occurs in each state, because it may mean that investing in renewables in one place has a better greenhouse outcome compared with renewables in another.

I agree. As I mentioned above, I believe Australia has a great opportunity to conduct such as study very well. I’d like to see it managed by AEMO, not by those who have an interest in trying to promote either renewables, or gas or coal.

This new post, posted today, may be of interest if you haven’t seen it already:


“Peter Lang, on 26 May 2010 at 13.36 Said:

Tim Kelly,

I forgot to mention cost per tonne CO2 avoided:

Wind, OCGT & CCGT = $50/t CO2-e avoided
CCGT only = $22/t CO2-e avoided”

Check out . Since last year, when the price crashed from $7.60, the cost of purchasing offsets has been $0.10/mt. LOL

That’s about 0.2-0.4% of the cost you quote.

Of course, CO2 is entirely benign, and its production should be subsidized, if anything.


Peter Lang,

I would very much support AEMO taking on this role to quantify the level of non renewable fuel burning that doesn’t get displaced by renewables. For me that would help to quantify the portion that does, hopefully on an annual basis.

On the ACCC, you would not have seen my submission bacause as you said, the submissions were not made public.

GreenPower also, did not make the submissions on the 2010 GreenPower Rules public and said that there “There were no objections received to the changes made on this occassion”, despite my submission which did exactly that.

The Commonwealth Ombudsman response to my complaints about the ACCC on GreenPower is that ” In the absence of any judicial determination of the Act [being the National Greenhouse and Energy Reporting (NGER) Act, its Determination, Technical Guidelines, NGA Factors Accounts and how they interact with the Trade Practices Act], it was not unreasonable for the ACCC to adopt the views of the department [being the DCC, now DCCEE].

So even if material is promoted by the ACCC, GreenPower or DCCEE that is totally contrary to fact or NGERS, there is no accountability or review of the materiality of complaints unless the matter is taken to the Federal Court by a party that could fund taking on the Government.

Regardless of where we may differ on a role for renewables, I am pleased to see that we share a willingness for disclosure and accountability. I just don’t know how we can get there.


I am presently completing a rebuttal of some beautifully-expressed complete nonsense prepared by an official from Sustainability Victoria. This nonsense has been provided to Panels Victoria in the matter of a 242 wind-turbine proposal for a region called Stockyard Hill (near Ballarat, I believe). The Panel had called for some “expert” advice on claims made in a submission of mine and that of another, which referenced and included a copy of a paper by Peter Lang ( ). I had expressed concerns about the likely impacts on grid stability and controllability and questioned the claimed GHG offsets that would result from this windfarm development. Peter’s paper (no reference to the paper was given by the official, except the author’s name), addressed wind’s intermittency and need for gas-turbine backup. The SusVic official dismissed the claims in Peter’s paper re intermittency. He did think to refer the matter to the AEMO for its view.

A Mr Oakeshott of the AEMO offered written advice that, in essence, stated the status quo, dismissed Mr Lang’s claims as being wide of the mark, not of concern, and anyway, we can trust the market to adjust to any contingencies that might arise from the increase in renewables required to meet the 20% renewables target. He left out a lot of material from presentations by AEMO people (including his own!) to recent industry conferences which, to my mind, firmly support Peter’s case.
From its recent presentations, the AEMO seems to me to see as its charter that it is there merely to find the technical fixes to implement government policy.
It doesn’t seem to take on the role of the public service providing fearless advice and/or criticism of government policy where necessary.

What I am saying is that, as a result of this exercise, I would NOT support the AEMO conducting a study into GHG offsets unless it was under very tight direction of such as a set of firm guidelines from its boss, the ACCC, and knew in advance that its findings would be open to public scrutiny by the mechanism of cross-examination.

Sadly, this matter of determining GHG offsets will have to come down to a full Public Inquiry. Peter, we are back to seeking a re-opening at the very least, of the “Misleading claims about carbon offsets” investigation, but expanding its role to that of a full Parliamentary Inquiry.


Paul Miskelly,

I agree that there would need to direction and overview of AEMO to undertake this review of how much renewables are reducing greenhouse gas emissions in state grids.

The ACCC has demonstrated however, that it does not understand greenhouse gas emissions accounting and accepts anything that Government agencies say without legal or numerical consideration.

We will still have a problem unless the reviews are supervised by a truly independent group that understands scope 1, 2 and 3 greenhouse accounting.


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