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REF Blog

Thermo-Economics

REF's director, John Constable, has just published an article "Thermo-Economics: Energy, Entropy and Wealth" in the journal of the Economics Research Council. This piece attempts to explain the relationship between thermodynamics and the theory of wealth in economics. From this perspective Dr Constable then argues that government attempts to drive an energy transition ahead of the learning curve and against the cost gradient and dangerous and likely to be reduce well-being as well as creating political discontent.

 

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REF on Guardian Constraints Story

On the 3rd of April the Guardian published a short article on constraint payments to wind power in Scotland ("Gas company special payments dwarf constraint payments to wind farms"). This story was based in part on a story in The Times earlier in the week ("Wind farms are paid £8.7m in one month to stop turbines"), and partly on an interview with REF.

The Guardian does not seem to have fully explained the significance of these extra payments to wind power, or the relation between payments to wind to stop and payments to conventional generators to start generating. REF sent the following letter to the editor, which has not, as far as we can tell, yet been published:

Dear Sir:

Your article (“Gas company special payments dwarf constraint payments to windfarms” 04.04.14) mistakenly downplays the significance of wind farms in Scotland demanding compensation well in excess of the subsidies lost when National Grid needs to stop them from generating. This is already very expensive and set to become more so.

The article also surprisingly implies that because conventional generation is paid to be constrained “on" to the system it is somehow acceptable for wind farms to overcharge per MWh when they are constrained “off".

However, such a view not only glosses over the economic and technical differences between constraining generation “on” and constraining it “off", but also fails to recognise the causal relation between these two actions, namely that constraining off wind farms on one side of a grid bottleneck, means that conventional generators on the other side, often gas, must be constrained on to maintain continuity of supply.

Thus, a significant proportion of the constrained on payments received by conventional generators must also be attributed to the proliferation of wind farms in Scotland, where the Connect & Manage policy has permitted and even encouraged wind development to exceed grid capacity.

It is possible, perhaps likely, that some energy companies who own both wind farms and conventional generation are making unreasonable profits on both sides of the equation, but a lack of transparency in the reporting of electricity market data makes it impossible for those outside the industry to investigate this matter.

The consumer is clearly vulnerable to unchecked exploitation at present, and strong intervention by government and the regulator, Ofgem, is long overdue.

Yours sincerely,
John Constable.

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New Monthly Record for Wind Farm Constraints Payments

It is now three years since the Renewable Energy Foundation revealed the growing problem of excessive prices charged by wind generators in Scotland to cease generation. However, and in spite of an intervention in February 2014 by the Minister of State for Energy, Michael Fallon, MP, there is no sign that the wind industry is willing to deal with this profiteering through self-regulation.

March 2014 has seen both the largest monthly volume of wind energy (107 GWh) constrained off the GB electricity system, and the largest monthly amount paid for wind farms not to generate (£8.7 million), as can be seen in the following chart, which also shows the steadily increasing trend over time.

Wind farm constraints are essentially caused by difficulties in exporting excess wind electricity generated in Scotland. In March 2014 approximately 12% of the potential wind power output of large Scottish grid connected wind farms had to be constrained off the system, thus incurring costs to the consumer in the form of constraint payments. Griffin wind farm showed the greatest reduction in output with more than 60% of its potential output in the month constrained off. 

The average price charged by the wind farms to reduce output was £80/MWh. This is almost double the lost income (a price of about £45/MWh to compensate for lost subsidy would be justifiable in the current market arrangements).

The prices charged in March this year range from £77/MWh to £149/MWh (full details by wind farm and settlement period can be found on the REF site: http://www.ref.org.uk/constraints/).

It is these excessive prices that Mr Fallon sought to address with his letter. But the industry does not appear to have taken any notice whatsoever, and while we understand the reluctance of government to intervene in the setting of prices in any part of the market, it is clear that wind power constraints are a special case, arising from the market distorting effects of state income support subsidies to renewables, and that consequently the time for vigorous government intervention has now come.

The scale of the growing threat to the consumer interest can be appreciated from the following charts, which record quarterly total wind power constraint costs and volumes.

The first quarter of 2014 has seen £13.7 million paid to wind farms to reduce output, which is a record in itself, but also confirms concerns that there is a trend towards consistently high constraint payments over the last year.

We are aware that the wind industry and some renewables sector journalists are still attempting to conceal the scale of this market abuse, by claiming that wind power receives less in constraint payments than conventional generation. This is untrue, and fails to convey the significant distinction between payments to conventional generators to START generating (in the event of unexpectedly high demand, for example), and additional payments to wind power to STOP generating. As we explained in a letter to The Times in January:

Conventional generators (coal and gas for example) are not paid extra to stop generating. Indeed, because of avoided fuel consumption they pay back to the system when constrained off. Wind power, on the other hand, loses subsidy when it is told to stop generating, and therefore asks for compensation, and in practice wind farms ask for compensation well in excess of the lost subsidy. This excess is clearly an abuse of market power and should be investigated by the regulator, Ofgem.

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REF Comment on Staffell and Green

In December 2012 REF published Professor Gordon Hughes’ paper The Performance of Wind Farms in the United Kingdom and Denmark (http://www.ref.org.uk/publications/280-analysis-of-wind-farm-performance-in-uk-and-denmark).

This seminal paper used advanced but standard statistical techniques to estimate the rates of decline in performance over time. Professor Hughes found that the economic lifetime of wind farms in the UK was very much shorter than currently estimated, at between ten and fifteen years, with those in Denmark faring better but still declining significantly.

The study has attracted a great deal of attention, and its fundamental finding is not now contested. Decline in performance is real and should be taken into account by policy makers and investors since it has significant implications both for the subsidy cost of the current renewable energy targets, and for the levelised cost of wind electricity and thus the rate of return to capital.

The study has been the subject of considerable criticism, particularly with regard to the methods employed, and Professor Hughes has responded and defended his approach (for example here in response to Professor MacKay, Chief Scientific Advisor to the Department of Energy and Climate Change http://www.ref.org.uk/publications/303-response-to-professor-mackays-comments-on-wind-farm-economic-lifetime-research and here in response to remarks by a blogger, Mr Chris Goodall (http://www.ref.org.uk/ref-blog/304-professor-hughes-and-chris-goodall).

Other researchers have begun to follow the lead given by Professor Hughes, and Dr Iain Staffell and Professor Richard Green of the Imperial College Business School have recently published a paper in the journal Renewable Energy (http://www.sciencedirect.com/science/article/pii/S0960148113005727).

This study uses different methods, and though it confirms the finding that performance declines significantly over time, it reports a lower rate, of about 1.6% per year, with “average load factors declining from 28.5% when new to 21% at age 19.” Staffell & Green note that this has the effect of increasing the levelised cost of electricity from wind by 9%.

REF believes that the debate has moved on from whether wind farm performance declines with age, as that is clearly confirmed, to the technical issues involved in measuring the rate and profile of the decline. The Staffell and Green paper proposes an approach that compares actual output with ideal output based on interpolated wind data. The potential difficulties of this specification are outlined in the Appendix to Professor Hughes’s paper and are not resolved in the new paper. Hence, we are not convinced that the Staffell and Green’s approach is superior to the statistical methods employed by Professor Hughes.

In one respect, we believe that the Staffell and Green analysis is clearly inferior to the Hughes specification. Namely, their model does not allow for the effect of technical progress in the wind industry through improvements in operating and maintenance practices, which can be treated separately from changes in turbine design. This was built into the Hughes specification and few would dispute that such technical progress has occurred in the past.

Work carried out by Professor Hughes – and made available to Dr Staffell and Professor Green – shows that the rate of such technical progress has fallen markedly since 2008. The reason this matters is that Staffell & Green and Hughes have both confirmed that specifications that allow for such technical progress yield higher estimates of the rate of decline in performance with age than those, including the new paper, which do not. In statistics this is known as omitted variable bias.

In summary, REF’s view is that while the new paper makes a useful contribution to public discussion of the performance of wind farms, Staffell and Green’s methods are not statistically superior to those used in the Hughes study. Indeed, Staffell and Green’s specification contains an assumption that results in a significant downward bias in the estimate of the rate at which performance declines with age. We will provide fuller details of these points in due course.

24.02.14

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REF Statement on Constraint Payments

It appears from an article in the Sunday Telegraph for the 23rd of February 2014 that the Minister of State for Energy, Mr Michael Fallon MP, has written to the wind industry trade lobby, Renewables UK, instructing them that he will not tolerate the current demands for constraint payment compensation well in excess of lost subsidy.

 http://www.telegraph.co.uk/financialservices/utilities/Business-energy/10655742/Wind-farms-paid-30m-to-shut-down-during-high-winds.html

 The scandal of constraint payments to wind power was first revealed by Renewable Energy Foundation in 2011, and we have argued from the first that government and the regulator, Ofgem (to whom we wrote on the 6th of May 2011 suggesting an inquiry), must intervene to protect the consumer and the reputation of the energy sector.

REF publishes the only conveniently accessible data set on this important subject:

http://www.ref.org.uk/constraints/

The REF data pages have formed the basis for numerous stories in the UK and international press.

As a result of this publicity the average bid to reduce wind output has fallen very significantly from an average of more than £200 per MWh in 2011 to £86 per MWh in 2013.  However this average remains in excess of what is reasonable given that the subsidy forgone by onshore wind farms is approximately £50 per MWh.  Furthermore, the average price demanded masks the fact that there is a wide range of charges with 18 onshore wind farms charging less than £80 per MWh whereas 11 others charge from £81 to £162 per MWh not to generate.

We infer that by exposing the industry’s abuse of market power to public scrutiny we have saved the UK consumer many millions of pounds in fact and many more millions prospectively.

Mr Fallon’s intervention is to be commended, and will, we trust, reduce the consumer cost of wind power constraint payments to justifiable levels.

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REF Consultation Response on EMR

The following email was sent on the 13th of February 2013 to DECC as a formal submission to the consultation on competitive allocation of contracts of Feed-in Tariffs with Contracts for Difference (FiTs CfDs) under the Electricity Market Reform (EMR) package. 

This email is a response to the Consultation on Competitive Allocation:

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/271919/Competitive_allocation_consultation_formatted.pdf

1. Do you agree with the Government’s proposed list of “established” and “less established” technologies? 

Broadly speaking, we agree. However, we see no reason for thinking that onshore wind and solar and hydro projects of capacity less than 5 MW should be regarded as not established. If anything, the industry has more experience of developing such sites than very much larger sites.

While we understand that there may be other reasons for wanting to exclude small sites from the competitive allocation process, this goal could and should be achieved with a much lower threshold, for instance 500 kW.

In this context we note that government uses the Renewable Energy Planning Database (REPD) as the grounding for the view that there is ample renewable capacity in the pipeline, and that therefore competitive allocation can be introduced earlier than anticipated. On the basis of our own information and research we have concluded that the REPD almost certainly significantly understates the quantity of applications below 5 MW, particularly for wind and solar. Thus, we conclude a) that the case for competitive allocation is in fact even stronger than government believes, and that b) there is a strong case for reducing the “established technologies” threshold in order to achieve the overall aims of competitive allocation, namely constraining costs within the LCF and delivering value for money to the consumer.

In addition we would recommend that DECC undertakes detailed surveys of local authorities in order to improve the REPD.

2. Do you agree that the “established” list of technologies should be subject to competition from the outset of an allocation process as part of helping to manage the LCF and delivering value for money?

Yes, we agree. Delivering value for money to the subsidising consumer is a matter of the first importance, and should be given priority over industry sensitivities.

We note also that a prompt start to competition will avoid minimise the interregnum in which unintended consequences may manifest themselves.

 

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Professor Hughes and Chris Goodall

Last week the energy blogger Chris Goodall published, on two websites, a comment on Professor Hughes' study for REF on the degradation of wind turbine performance over time (See Carbon Commentary; and also the website of the Ecologist magazine).

Mr Goodall posed two questions, and invited a response. The following text is Professor Hughes' reply and has also been published on the Carbon Commentary site, where Mr Goodall's further comments, and those of others, can be read.

Wind Turbine Performance Over Time: A Response to Chris Goodall

In his blog published on 03.01.14, “Wind turbines – Going strong 20 years on”,[1] Chris Goodall argues that the degradation in the performance of wind turbines with age is much lower than reported in my 2012 study The Performance of Wind Turbines in the United Kingdom and Denmark.[2] The following note explains why I believe that my conclusions are sound.

Mr Goodall has kindly provided me with the data to which he refers to in his work. With the exception of a long series for Delabole wind farm, Mr Goodall’s data is a small subset of the much larger sample of wind farms, several hundred in fact, analysed in my original study. Mr Goodall’s data also adds a few monthly observations that were missing when my data was originally extracted from the source database. Overall, Mr Goodall’s data amount to about 5% of the data that I analysed, and where he has new material it adds very little.

Furthermore, Mr Goodall himself very frankly admits that he does not have the statistical skills required to replicate the methods of my analysis. His work does not constitute a reanalysis or a rebuttal of my paper. In fact, his calculations simply reproduce one feature of the results reported in my paper.  There was a generation of wind farms developed in the early 1990s, both in Denmark and the UK, using turbines of less than 0.5 MW which have experienced a relatively limited decline in performance with age.  By focusing exclusively on these wind farms, Mr Goodall misses the bigger picture.  The performance of wind farms developed from the mid-1990s onward is much worse.  The average size of the turbines and the wind farms increased.  The larger turbines appear to have been less reliable, while my analysis suggests that the siting and maintenance of wind farms may have deteriorated.  

Mr Goodall concludes with two challenges/questions which are representative of many comments on my work.  They spring from a lack of understanding of the statistical reasoning involved.  I will begin with his second question, since it is central to the analysis. Mr Goodall wonders how it is possible to estimate the decline of load factors over time when we have less than twenty years of data for any wind farm. This is where the mathematical/statistical specification described in the Appendix to my paper is crucial.

The load factor for any wind farm in any period is expressed as the sum (or product in the multiplicative version) of components associated with the age of the wind farm (held constant over all wind farms of the same age), the period (constant over all wind farms in one period), the site of the wind farm (constant over time and age), and a random error. This is a standard formulation used by statisticians, including for the analysis of data from a wide range of medical and biological trials. The age effects can be identified from the variation in output across wind farms of different ages for each month. So long as each wind farm is tracked for a number of periods, the site characteristics of the wind farm can be separated from age effects which are common to all wind farms of the same age.

In his first question, Mr Goodall challenges me to produce a counter-example to the case of Delabole, which he claims demonstrates a much lower rate of degradation with age than that reported in my paper (in fact it is similar to the overall rate I report for Denmark). This is a recurrent theme among critics of my work. As an argument it is equivalent to someone claiming that smoking cannot harm anyone’s health because their “Uncle Jack” has smoked a pack a day for 60 years and is still fit and well at an age of 80. Of course there are apparent counter examples, and these can be found in the REF load factor database: www.ref.org.uk. It would be invidious to name them, and in any case they no more prove my analysis than Delabole disproves it. Individual cases prove nothing about population epidemiology, a point which is as true for wind power as for public health. The proof is in the statistical analysis itself.

As a separate point, I am struck by how selectively critics report the results of my work. As noted above, the experience of Delabole and other wind farms built in the period 1991-93 is consistent with my analysis of wind farms in Denmark, where load factors seem to decline more gently with age. That may reflect the robustness of wind turbines built in the early 1990s, site choice, how they have been maintained, and other factors. For the avoidance of doubt, I do not argue that the performance of wind farms must, inevitably, degrade rapidly with time. My observation is that the average performance of wind farms in the UK has, as a matter of fact, fallen as they have aged, a fact that is probably the result of both the physical characteristics of wind power and the economic characteristics of the financial incentive regime, the Renewables Obligation subsidy.

My results have important and obvious implications for both investors and policymakers. But the response of advocates of wind power is rather interesting. For the most part, it has involved an attempt to shoot the messenger rather than trying to understand the underlying phenomena. Yet, none of the statistical analyses of my or other data have demonstrated that there is no degradation in performance in age. The issue is not whether degradation occurs, but how much. There can be reasonable disagreement about that, as the comparison between Denmark and the UK illustrates (which is why I included that in my original study). The key point is to identify the causes of changes in load factors over time revealed by statistical analysis, and whether and how these may be addressed.

The willingness of the owner/operator of Delabole to provide unpublished data on output from the wind farm is to be commended, but, though welcome, it is only a small step in the right direction. Any investigation in this area is hampered by the unwillingness of operators to provide the wind speed data collected by the anemometers which are installed at all wind farms. Let me briefly indicate why this matters. One explanation for performance degradation over time would be an increasing frequency (or length) of mechanical failures of turbines. An alternative explanation is that the power curve (the relationship between wind speed and power output) changes due to gradual erosion of the blades, a phenomenon well known in the industry. An assessment of the relative contribution of these – and other – factors can be used to improve both turbine designs and maintenance regimes for existing wind farms, but such work cannot happen until the anemometry data from individual wind farms is made publicly available.

An ostrich-like approach of denying that there is a problem helps no-one. A lack of transparency leads to the suspicion that wind operators are unwilling to be accountable for the large sums of public money which they are currently receiving, and certainly makes it difficult to ensure that subsidy policies give good value for money to the consumers who foot the bill. But even the wind industry does not benefit in the long run, because it is foregoing the opportunity to learn from and build on the lessons from detailed analysis of performance.

Gordon Hughes

05.01.14

About the Author

Dr Gordon Hughes is a Professor of Economics at the University of Edinburgh, where he teaches courses in the Economics of Natural Resources and Public Economics. He was senior adviser on energy and environmental policy at the World Bank until 2001.



[2] Gordon Hughes, The Performance of Wind Turbines in the United Kingdom and Denmark (Renewable Energy Foundation: London, 2012). Available for download at www.ref.org.uk.

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Emissions Savings' Potential of Wind and Solar Power

REF is often asked about the lifetime emissions saving potential of uncontrollable renewables such as wind and solar, the output of which is difficult to predict with great accuracy even a few hours ahead.

Given uncertainties about the embedded emissions in site specific applications of these technologies, which may vary considerably (due to difficult access or disturbance of peat, for example), it is inherently very difficult to give a generally adequate answer.

Moreover, it is not clear how solar and wind generators interact with the conventional plant in the rest of an electricity system. To be specific, there are uncertainties a) as to which conventional plant is likely to be displaced by wind and solar, and, b) if it is fossil-fuelled plant, whether the thermal efficiency of plant is significantly degraded by the ramping of output required when operating in the support role.

In relation to the first of these points, the plant likely to be displaced, REF has consistently suggested that the uncertainties are such that analysis should presume only a range of values for emissions saved, from the lowest, associated with gas, to the highest associated with coal, with a grid average emissions factor being used for approximate quantitative calculations. However, it should be recognised that the grid average emissions may not reflect the most probable displacement scenario at any one time.

Careful examination of the GB fuel mix data (published by REF) in recent months confirms this approach, and indicates that gas, which is currently the plant that ramps up and down most to meet consumer demand, is also the plant that is most likely to be displaced by wind. Only a statistical analysis could confirm this claim, but the indicative evidence is highly suggestive.

Consider, for example the fuel mix on the 5th of November this year:

Click here for access to REF's web application showing historic fuel mix data for this date.

Note the fact that from period 19 to period 31 load on the system was steady at approximately 43 GW. Output from coal and nuclear is steady over the period, while gas declines significantly between periods 27 and 31, a decline that corresponds with a significant increase in output from wind.
Since load and coal and nuclear output are all stable over this period, it is reasonable to infer that the decline in gas generation is a response to the increase in wind output. In other words that wind power was displacing gas at this time.

This effect can be more clearly seen in the following plot which shows gas and wind contributions alone.

 Click here for this view of the data on REF's web application showing historic fuel mix data

Such data confirms our view that when assessing the likely emissions savings from a wind project, particularly in the planning system where benefits must be weighed against disbenefits, coal displacement should be regarded as an unlikely outcome, with gas being the likeliest displaced fuel, with grid average emissions savings being used only as a very rough rule of thumb.

Here is a worked example for a 2.3 MW wind turbine working at 27% load factor.

2.3 MW x 8760 (hours in a year) x 0.27 = 5,440 MWh

Assuming emissions displacement at the grid average in 2011, which was 0.45 tCO2/MWh, this would save about 2,500 tonnes of CO2 per year.

This is approximately 0.0003% of the UK's total emissions of 722,076,000 tonnes of CO2 (production emissions and consumption emissions combined, as reported by DEFRA.  For discussion see DEFRA, UK's Carbon Footprint 1993-2010 (Dec. 2012),

The emissions per MWh of coal and gas vary from plant to plant, and according to character of operation, but figures of 0.95 tonnes CO2 per MWh for coal (though supercritical coal will perform better), and 0.4 tonnes CO2 per MWh for the UK's current combined cycle gas turbines (though the more modern Combined Cycle Gas Turbines currently now entering the market will perform better), give an approximate sense of the relative emissions (this is discussed at some length on page 15ff of David White's 2004 study for REF.

Thus if our sample wind turbine were to displace coal it would save about 5200 tonnes of CO2 per year; whereas it were to displace gas generation it would save about 2,200 tonnes per year.

These are obviously significant differences in magnitude, and have very significant effects on the wind power subsidy cost per tonne saved.

 

 

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Are Fossil Fuels Subsidised in the UK?

In discussions of subsidies to renewables it is sometimes claimed that fossil fuels in the United Kingdom receive greater support. This misunderstanding arises from the confusion of two quite different things:

a) subsidies to investors in renewables which increase consumer costs

and

b) Lower VAT (5% not 20%) on gas and electricity used by domestic energy consumers, and tax breaks to oil and gas companies, both of which will reduce costs to consumers.

It is obviously misleading to treat these two effects as if they were similar in economic character. However, this is increasingly common, even amongst those who might be expected to understand these matters.

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Constraint Payments: Misunderstandings and Misrepresentations

REF was the first organisation to draw attention to the excessive prices demanded by windpower to reduce output (constraint payments), and the resulting publicity is in part responsible for the fall in prices, though these are still, in our view, excessive.

The wind industry has responded to this criticism by attempting to confuse the public with claims that other generators are paid more to be constrained off. This is untrue, but unfortunately was made the central argument in a piece in the trade journal, Utility Week:

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