Wind Power - A Rising Capacity Factor. Really?

The Capacity Factor (or annual fraction of maximum output achieved) has come to dominate the credibility of wind power schemes. The wind industry vigorously promotes the idea that the Capacity Factor (or CF) is rising. They eulogize wind power as an improving and developing technology. 

CF  has become the de facto metric by which energy generation is measured by. So a wind turbine system displaying a rising CF would undermine the growing view that wind is actually a moribund and subsidy addicted dead end. 

So there is a lot to play for by the wind turbine aficionados. Especially as today if you look at UK offshore wind turbine data it does look like the CF for later offshore wind farms in the UK is going up.

So is this due to an improving dynamic and forward looking technology?

Or is there something else going on here? Is this simply a “fix” - a manipulated figure. More smoke and mirrors to defend a stagnating technology?

While many factors ultimately determine the output of a wind turbine, the maximum output from a wind turbine is mostly determined by the the diameter of its rotor, the hub height and its location.

Yet the published Maximum Capacity (and so the calculated CF) of a wind turbine is determined from the size of the generator NOT from size of the rotor. Yet in reality the size of the attached generator is really a secondary limiter. It is rarely (if ever) run at maximum output and so makes little or no difference to the actual generation capability of the turbine.

The generator spends almost all of its life being driven at one fifth to one third of its maximum output. With this level of headroom, the CF is wide open to manipulation. It can easily be increased by reducing the relative size of the generator to the turbine swept area so that the smaller generator is driven harder and so shows a higher CF without actually increasing annual output. (In fact if you decrease the generator size too far you may push up the CF yet reduce the total energy output over the year.)

So is this happening to UK offshore wind? Are newer turbines being de-rated to increase the CF which will create the illusion that the technology is advancing? Has the Wind Industry any other potential motives as well?

It appears so.

Take the Walney Offshore Wind Park run by Dong Energy in the UK.

Walney consists of two phases. Walney One was commissioned in 2011 and Walney Two was finally commissioned in 2012. Both are now fully operational.

Walney One and Walney Two have 51 turbines each. All the turbines are rated at 3.6MW Maximum Capacity. But the turbine models are different.

Walney One uses Siemens SWT-3.6-107 turbines. These are 137m high, with a swept area of 9000m2 which gives a area/power density of 2.4 square meters per KW

The second tranche Walney Two uses Siemens SWT-3.6-120 turbines. These are 150m high, have a swept area of 11,300 square meters and a area/power density of 3.14 square meters per KW.

Essentially, while they both have the same size generators, Walney Two has bigger turbines.

Unsurprisingly, Walney Two has declared a higher capacity factor than Walney One. But given the quite large difference on swept area, the difference in CF is strangely small.

While the area power density differs by 30% the CF in the last year differs by less than 5%

If you normalize the turbine generator size on the area/power density of the Walney One turbines, (i.e so Walney Two would have an area/power density of 2.4 sqm/KW) then the Walney Two turbines should be rated and fitted with at least a  4.7MW generator.

If this was the size of generator attached to the Walney Two turbines then the capacity factor for last year (based on the 4.7MW generator size) for Walney Two actually decreases to a lowly 34%.

So then you have to ask: Why are these bigger turbines at Walney Two (in reality) being worked significantly less hard than their Walney One cousins? Why are they trading down the magnitude of the increased Capacity Factor?

Here I believe we have the second hidden agenda item associated with de-rating these turbines.

There have been long term and apparently intractable generic reliability problems with offshore wind turbines especially when under significant load. (see earlier post Here) So the trick to making your turbines avoid (example) catastrophic and immensely expensive gear box failure is to de-rate them and run them as far below their capability as is economically and practically possible. Even though the operator is paid around £150 per MWh, losing a gearbox will make a big dent in their profitability.

So for the wind industry, quietly fitting smaller generators to your turbines is a win-win. It falsely promotes the impression that turbine capacity factor has magically increased, while at the same time allowing them to de-rate these larger turbines and run them less hard so reducing costly repair and maintenance.

What this highlights is that the “maximum capacity” (based on generator size) as promoted by the wind industry is actually a fictitious value and bears little relationship to turbine capability or size. Calculating the effectiveness of wind turbines on this false flag is disingenuous.

So next time you hear some pro-wind zealot breathlessly announce that capacity factors are going up to 50% (and beyond) just ask them what the area/power value for this wondrous advance in turbine design is. I suspect they will look at you blankly.

Tell them that if they want to prove wind turbine capacity factor is significantly improving they need to compare LIKE with LIKE. But warn them, that if they do actually compare like with like, their magical improvements will most likely completely disappear. If not go backwards.

Is there Something (Else) Wrong with Wind Power?

We all know wind power is intermittent. I thought I would take a look at how predictable windpower intermittency is and how accurate wind power output predictions are.

In the process I think I have tripped over a new issue regarding wind generation (but more on that later).

The bmreports site (HERE) has a section on wind generation and shows a graph of an original output prediction, a more recent and accurate revised prediction and also the actual out-turn.

The original forecast value is done 41 hours before the start of the forecasted day. The revised forecast is done 4 hours before the start of the forecasted day. The predictions use weather forecast data for the known wind farm locations and factor in a range of other parameters. These are sophisticated predictions and are probably as good as they get.

Here is a few example snap shots taken in the last month from the bmreports site.

But as well as this continuously updated graph, bmreports also publish the same 3 day data as an xml file. I've collected the xml files for one month. (Annoyingly I missed two days so these have been left out. But even so I think this is quite a good data set.)

Above is a graph of this data showing the final revised prediction done 4 hours before the start of the predicted day (red) and the final out-turn (blue).

(I've left out the original prediction as for obvious reasons, it was more in error of the final out-turn and so added little to the graph). Note: Actual metered capacity is actually 8972MW so the graph is unduly kind stopping at 8000.)

The first thing that can be seen is that the out-turn is often (not occasionally) in significant variance with the predictions. The graphs may be the same shape but the values at any one point in time are often significantly different. Clearly, any system with a large wind component that relied completely on even a near term forecast (and without spinning reserve) would soon end up in deep trouble.

So whatever the pro-wind zealots preach on Twitter, the problem with lack of wind power predictability has not gone away. Neither has its intermittency.

But potentially the example bmreports graphs (as well as mine) also show another problem. 

Notice in the above graphs how on the occasions the wind output rises above about 30% capacity (3000MW), during the rise, the out-turn lags the predictions and the maximum out-turn is significantly less than either of the predictions. 

It is as if a large proportion of wind turbines exposed to a rising wind and high wind periods are being feathered (or throttled back) for some reason during these periods.

At lower wind speeds there are still periods of great discrepancy between prediction and output but the tracking between prediction and output does appear more coherent. (Remember this forecast was done 4 hours before start of predicted day!)

Wind energy companies only get paid when they are generating. So why would they throttle back their turbines in high winds?

And the answer to that I believe is good old repair and maintenance.

For almost any machine, if you run it lightly it lasts longer. Take a car. The harder you drive a car the more wear and tear it suffers. Just about all rotating machinery obey this simple rule – including wind turbines.

We know that there is a severe generic problem with wind turbine gearbox reliability. (See This Post - The Ghost in the Gearbox and Post - More Ghosts in the Gearbox )

I would suspect that it has been found that if the loading on a wind turbine gets above a certain value the wear rate and maintenance/repair cost will be far more than the return from the extra energy generation.

So maybe operators are unilaterally and quietly deciding that when the wind gets too changeable or too strong, the turbines will be run at reduced output compared to what they are supposed to be capable of.

Wind turbines are capital intensive. If you suffer a catastrophic failure you will ruin the huge and guaranteed profit (subsidy included) your turbines can make. Do it too many times and you may end up going bust. Better to ignore the whole reasoning, propaganda and hype associated with why the thing was built in the first place and go for the low hanging fruit.

Remember most windfarms have a 25 year subsidy regime locked in place. It's a nice little earner. Operators are going to do whatever it takes to maximise the financial gain over this period and if that includes reducing output to make their gearboxes and other expensive components last a bit longer then they will do it. The abatement of Carbon Dioxide can go to hell.

This, of course, makes an even bigger mockery of the often hyped “Installed Capacity” figure than it already is. It also shows how the unreliability of these machines impacts the supposed reason they were built.

It means that wind power is perhaps even more useless and under-achieving than first thought.

I cannot prove the operators are intentionally throttling back their turbines to reduce their maintenance bills. 

But I bet I'm right.