Resource Documents: Economics (162 items)
Documents presented here are not the product of nor are they necessarily endorsed by National Wind Watch. These resource documents are provided to assist anyone wishing to research the issue of industrial wind power and the impacts of its development. The information should be evaluated by each reader to come to their own conclusions about the many areas of debate.
Author: Nelson, Donna
RE: Open Meeting Agenda Item 29; Project No. 42079; Discussion and possible action on electric reliability; electric market development; ERCOT oversight; transmission planning, construction, and cost recovery in areas outside of ERCOT; SPP Regional State Committee and electric reliability standards and organizations arising under federal law.
As discussed at the April 17th open meeting, I would like to open a project to look at ERCOT’s prospective system upgrades, ancillary services, and the transmission planning process related to renewable resources, as well as problems that have arisen as part of the CREZ build-out. The unique characteristics and often-remote locations of renewable resources pose challenges to the electric grid, and those challenges are increased as the volume of wind on the system increases. For example, some of the series compensated transmission lines that are part of the CREZ build- out can cause sub-synchronous oscillation issues that must be resolved in order to avoid damage to the transmission grid and generation resources. The Panhandle region is currently experiencing so much interest from wind developers that there is a concern that the overall system strength will be negatively affected unless the infrastructure is updated.
The Federal Production Tax Credit was started in 1992 in order to spur a developing technology and allow it to gain the momentum necessary to make it commercially viable. Now, 22 years later, there can be no doubt that renewable technology-especially wind and solar-are mature industries. Every year when Congress extends the Production Tax Credit we are told that it will be the last year. Although the credit expired in December, the Senate Finance Committee recently approved a $13 billion, two-year renewal. I fear that this credit will once again be extended.
The Federal Production Tax Credit distorts wholesale electric markets, including the ERCOT market. With wholesale rates that hover around $40 per MWh in ERCOT, a federal program that pays wind generators $23 per MWh ultimately destroys the economic underpinnings of the wholesale competitive electric market. As wind installations continue and wind capacity in our market becomes a larger percentage of ERCOT capacity, not because it makes sense from an economic standpoint but because investment is driven by a federal government subsidy, our market faces the very real possibility of losing base load generation. As former Senator Phil Gramm stated in a December 25, 2012 Wall Street Journal article: “The costs of wind subsidies are extraordinarily high – $52.48 per one million watt hours generated, according to the U.S. Energy Information Administration. By contrast, the subsidies for generating the same amount of electricity from nuclear power are $3.10, from hydropower 84 cents, from coal 64 cents, and from natural gas 63 cents.”
While this Commission has no ability to change what Congress does, we do have an obligation to Texans to periodically review whether our rules appropriately assign cost to those who cause those costs. I would like to explore the costs of system upgrades, the costs to maintain and operate the current system, and the allocation of those costs specifically related to renewable resources.
Some of the transmission lines built as part of CREZ include series compensation that has the potential to cause sub-synchronous oscillation if the series capacitors that have been installed are taken out of bypass mode. This issue is a consequence of expanding the system to access resources that are located far from load centers. This Commission needs to decide how to address the existing problem, how to avoid this problem in the future, and how to resolve the cost allocation issues o f mitigating this risk.
Due to the amount of wind generation that we are now expecting on the transmission lines in the Panhandle, stability concerns and weak system strength will present significant challenges in that area. ERCOT has released a study that recommends system upgrades to address this issue. The transmission facilities in the Panhandle region installed as a part of CREZ included reactive equipment to support 2,400 MW of wind. As we see wind online in excess of 2,400 MW, the system strength will suffer. Under weak grid conditions, a small variation of reactive support results in large voltage deviations. These potential grid stability issues raise fundamental policy questions. For example, should we ask electric customers to fund further investment in the transmission system to improve stability or should some of the risk be borne by generators? When I review the PURA provisions that approved construction ofthe CREZ lines, it is obvious to me that the Texas Legislature intended that wind developers should have skin in the game but we need to further flesh out what that means as wind generation becomes an increasingly large percentage of installed capacity in the ERCOT market.
ERCOT is currently evaluating an ancillary services redesign, which gives us an opportunity to examine our current mix of services, those contemplated for the future, and the costs associated with these products. One of the reasons that ERCOT is exploring potential improvements to ancillary services is because some new resources expected to be added to the ERCOT system bring with them additional challenges. Given ERCOT’s changing resource mix, I would like to look at whether there are ancillary services costs that are incurred specifically because of the unique nature ofrenewable resources.
The ERCOT Board instructed ERCOT to review its transmission planning process. One issue
that I would like to explore here at the Commission is whether the production cost savings test, most recently adopted by the Commission in March 2012, is appropriate for analyzing the
benefits of transmission projects, especially projects to address transmission limitations and voltage stability mitigation that will be needed to address a system heavily weighted with wind generation, with a production cost ofzero.
I request that Commission Staff open a project with the title “ERCOT Planning and System Costs Associated with Renewable Resources.” If we encounter major policy issues in this rulemaking that we believe cannot be resolved by PURA, we can seek Legislative guidance by including these topics in our Scope of Competition report.
I look forward to discussing this with you at the open meeting.
TO: Commissioners Kenneth W. Anderson, Jr., and Brandy D. Marty
FROM: Chairman Donna L. Nelson
DATE: May 29, 2014
Author: Poser, Hans; et al.
Over the last decade, well-intentioned policymakers in Germany and other European countries created renewable energy policies with generous subsidies that have slowly revealed themselves to be unsustainable, resulting in profound, unintended consequences for all industry stakeholders. While these policies have created an impressive roll-out of renewable energy resources, they have also clearly generated disequilibrium in the power markets, resulting in significant increases in energy prices to most users, as well as value destruction for all stakeholders: consumers, renewable companies, electric utilities, financial institutions, and investors.
Accordingly, the United States and other countries should carefully assess the lessons learned in Germany, with respect to generous subsidy programs and relatively rapid, large-scale deployment and integration of renewable energy into the power system. This white paper is meant to provide further insight into the German market, present an objective analysis of its renewable policies, and identify lessons learned from Germany, and to a lesser degree, other European countries.
The rapid growth of renewable energy in Germany and other European countries during the 2000’s was due to proactive European and national policies aimed at directly increasing the share of renewable production in their energy mixes through a variety of generous subsidy programs. Two main types of subsidy programs for renewable power developed in Europe include feed-in tariffs (FITs), which very quickly became the policy of choice for Germany and many other European countries, and quota obligation systems.
FITs are incentives to increase production of renewable energy. This type of subsidy guarantees long-term (usually for 20 years) fixed tariffs per unit of renewable power produced. These fixed tariffs normally are independent of market prices and are usually set by the government, but can be structured to be reduced periodically to account for technology cost decreases. The level of the tariffs normally depends on the technology used and the size of the production facility. Because of their generosity, FITs proved capable of quickly increasing the share of renewable power, but since the FITs are set administratively, it is difficult to meet renewable energy goals in the most cost-effective way possible.
The quota system is the European equivalent to the Renewable Portfolio Standard used in the United States. Whereas FIT programs set the price for the resources and let the market achieve whatever level it can at that price, the quota system is a market based system that sets the desired amount of renewable resources and lets the market determine its price. Under the quota system, compliance is proven through renewable certificates that can usually be traded.
Germany used FITs to help finance its energy policy, “Energiewende” (the energy transformation), that calls for a nuclear-free and carbon-reduced economy through a vast deployment of renewable technologies.
Because FITs levels were administratively driven and slow to adapt to the evolution of the solar market, the incentive became excessively generous, which initiated an uncontrolled development of renewables, which, in turn, created unsustainable growth with a myriad of unintended consequences and lessons learned. Accordingly, this analysis will focus on Germany, whose FIT policies allowed it to realize the highest production of non-hydro renewable electricity (wind and solar) in Europe.
The most important lessons learned include:
- Policymakers underestimated the cost of renewable subsidies and the strain they would have on national economies. As an example, Germany’s FIT program has cost more than $412 billion to date (including granted and guaranteed, but not yet paid FIT). Former German Minister of the Environment Peter Altmaier recently estimated that the program costs would reach $884 billion (€680 billion) by 2022. He added that this figure could increase further if the market price of electricity fell, or if the rules and subsidy levels were not changed. Moreover, it is estimated that Germany will pay $31.1 billion in subsidies for 2014 alone. A recent analysis found that from 2008 to 2013, Germany incurred $67.6 billion (€52 billion) in net export losses because of its high energy costs, compared to its five leading trade partners. Losses in energy intensive industries accounted for 60 percent of the total losses. This was further highlighted by a recent International Energy Agency report, which stated that the European Union (EU) is expected to lose one-third of its global market share of energy intensive exports over the next two decades due to high energy prices, expensive energy imports of gas and oil, as well as costly domestic subsidies for renewable energy.
- Retail prices to many electricity consumers have increased significantly, as subsidies in Germany and the rest of Europe are generally paid by the end users through a cost- sharing procedure. Household electricity prices in Germany have more than doubled, increasing from €0.14/kilowatt hour (kWh) ($0.18) in 2000 to more than €0.29/kWh ($0.38) in 2013. In Spain, prices also doubled from €0.09/kWh in 2004 to €0.18/kWh in 2013 ($0.12 to $0.23) while Greece’s prices climbed from €0.06/kWh in 2004 to €0.12/kWh in 2013 ($0.08 to $0.16). Comparatively, household electricity prices in the United States average $0.13/kWh, and have remained relatively stable over the last decade.
- The rapid growth of renewable energy has reduced wholesale prices in Germany, with adverse consequences on markets and companies. Large subsidies and guaranteed interconnection to the grid for renewable energy led to unexpected growth over the last 10 years in Germany and elsewhere. The merit order in Germany’s wholesale markets switched as renewables, with a zero variable cost of production, take precedence over thermal plants. As a result, wholesale prices in Germany for base load have fallen dramatically from €90-95/megawatt hour (MWh) in 2008 to €37/MWh in 2013. This has created a large amount of load and margin destruction for utilities that built and financed thermal plants. Many new gas-fired power plants have been rendered uneconomical, leaving owners to shore up their balance sheets by undertaking large divestitures of some of their holdings, as well as by reducing their operational costs. The impact to utilities’ shareholder value has been dramatic and has come on top of the impact of the global financial crises, and, in the case of Germany, the decommissioning of nuclear power. The German utilities have seen their stock plunge by nearly 45 percent since 2010. Some power plant operators in Germany and other countries, like the United Kingdom, are now calling for capacity payments to ensure that reliability is maintained and not threatened by the shutdown of various thermal power stations.
- The wholesale pricing model has changed as a result of the large renewable energy penetration. In the past, wholesale prices followed the demand curve, but in Europe they now react to the weather; going down when the sun shines and the wind blows, and up when—at times of high demand—the sun does not shine and the wind does not blow. Price forecasts and power trading require more skill sets and different know-how, including weather forecasting.
- Fossil and nuclear plants are now facing stresses to their operational systems as these plants are now operating under less stable conditions and are required to cycle more often to help balance renewables’ variability. Investments in retrofits will be required for these plants in order to allow them to run to these new operational requirements. Moreover, renewable resources are dramatically changing thermal plants’ resource planning and margins. As a result, many of these plants are now being retired or are required to receive capacity payments in order to economically be kept online.
- Large scale deployment of renewable capacity does not translate into a substantial displacement of thermal capacity. Because of the variability of wind and solar, there are many hours in the year during which most generation comes from thermal power plants, which are required to provide almost complete redundant capacity to ensure the reliability of the system. In turn, grid interventions have increased significantly as operators have to intervene and switch off or start plants that are not programmed to run following market- based dispatching. For instance, one German transmission operator saw interventions grow from two in 2002 to 1,213 in 2013. It is higher amounts of renewables with low full load hours relative to the total portfolio of power production that creates greater variability and strains on the grid. In the case of Germany, it is the large-scale deployment of both wind and solar that has impacted the entire system.
- Large-scale investments in the grid are being required to expand transmission grids so they can connect offshore and onshore wind projects in the north of Germany to consumers in the south of the country. The total investment cost for the build-out of German onshore and offshore transmission systems is estimated to be around $52 billion (€40 billion) over the next 10 years. Moreover, the grids are now being challenged to meet the dynamic flows of variable renewables and require significant additional investment to accommodate increased penetration of renewables. All of these costs will ultimately be passed on to electricity consumers. This has not gone unnoticed in Germany or in the EU. A report was released in late February 2014 by an independent expert commission mandated by the German government, which concluded that Germany’s current program of incenting renewables is an uneconomic and inefficient means to reduce emissions and therefore should be stopped. Moreover, the European Commission released new guidelines on April 9, 2014, with effect starting in 2017 that will correct market distortions. It will essentially ban all FIT subsidies and introduce technology agnostic auctions as the only incentives for renewables.
- Overgenerous and unsustainable subsidy programs resulted in numerous redesigns of the renewable support schemes, which increased regulatory uncertainty and financial risk for all stakeholders in the renewable energy industry. As the lessons above show, some European renewable energy regulatory regimes were inappropriately structured, gamed by market players, or made obsolete by market conditions. As a result, governments and regulators corrected unsustainable regulatory regimes by reducing the level of subsidies, sometimes retroactively, and modifying the rules of the programs. These changes often resulted in significant value destruction to various renewable players and their respective investors. This continued regulatory uncertainty across Europe is increasing the cost of capital to European renewable companies, which the rating agency Fitch just recently highlighted as the most likely sector in the European energy market to receive a downgrade in 2014.
These lessons learned are important and provide factual analyses to assist other countries’ electric industry stakeholders’ in creating more technically-efficient, cost-effective and sustainable ways to integrate renewable energy.
U.S. stakeholders should take into consideration the lessons learned from Germany and Europe:
Utilities should incorporate those lessons into their strategic planning, load forecasting, financial planning, trading, and regulatory affairs organizations. Decisions about current and future investments should then be made with this new analysis in mind.
Renewable companies should calculate appropriately the true costs of grid enhancements, capacity, and other important measures when submitting their plans to commissioners, investors, and other stakeholders.
Legislators and regulators should use the lessons learned from large scale integration of renewables in Germany and elsewhere in Europe to ensure a stable transition of renewables as part of the overall power portfolio while ensuring high reliability of power, stability of pricing to all users, as well as minimal value destruction to both utilities and renewable companies.
Finally, consumers must be made aware of the tradeoffs to a large portfolio of renewables and the necessary requirement for a smooth transition as part of the overall power portfolio.
In conclusion, the lessons learned in Europe prove that the large-scale integration of renewable power does not provide net savings to consumers, but rather a net increase in costs to consumers and other stakeholders. Moreover, when not properly assessed in advance, the rapid, large scale integration of renewables into the power system will ultimately lead to disequilibrium in power markets, as well as value destruction to renewable companies, utilities, and their respective investors. The U.S. has the opportunity to incorporate these lessons learned to ensure the sustainable growth of renewable energy over the long-term, for the benefit of all customers.
Felix ab Egg
FAA Financial Advisory (Finadvice), Adliswil, Switzerland
Author: Frank, Charles
This paper examines five different low and no-carbon electricity technologies and presents the net benefits of each under a range of assumptions. It estimates the costs per megawatt per year for wind, solar, hydroelectric, nuclear, and gas combined cycle electricity plants. To calculate these estimates, the paper uses a methodology based on avoided emissions and avoided costs, rather than comparing the more prevalent “levelized” costs. Three key findings result:
- First—assuming reductions in carbon emissions are valued at $50 per metric ton and the price of natural gas is $16 per million Btu or less—nuclear, hydro, and natural gas combined cycle have far more net benefits than either wind or solar. This is the case because solar and wind facilities suffer from a very high capacity cost per megawatt, very low capacity factors and low reliability, which result in low avoided emissions and low avoided energy cost per dollar invested.
- Second, low and no-carbon energy projects are most effective in avoiding emissions if a price for carbon is levied on fossil fuel energy suppliers. In the absence of an appropriate price for carbon, new no-carbon plants will tend to displace low-carbon gas combined cycle plants rather than high-carbon coal plants and achieve only a fraction of the potential reduction in carbon emissions. The price of carbon should be high enough to make production from gas-fired plants preferable to production from coal-fired plants, both in the short term, based on relative short-term energy costs, and the longer term, based on relative energy and capacity costs combined.
- Third, direct regulation of carbon dioxide emissions of new and existing coal-fired plants, as proposed by the U.S. Environmental Protection Agency, can have some of the same effects as a carbon price in reducing coal plant emissions both in the short term and in the longer term as old, inefficient coal plants are retired. However, a price levied on carbon dioxide emissions is likely to be a less costly way to achieve a reduction in carbon dioxide emissions.
Author: Hawkins, Kent
The nature of the short-term operation of an electricity system is more like that of a machine than a market.
A paper published by Joseph Cullen in the American Economic Journal: Economic Policy (November 2013), “Measuring the Environmental Benefits of Wind-Generated Electricity”  is important in two regards. First, using Texas data, it shows that even with notable emissions savings attributed to wind, the highly subsidized cost of wind is exceeded only by high estimates of the social costs of pollution.
Secondly and perhaps more importantly, his paper provides an opportunity to illustrate where wind-performance analyses fall short. This is the subject of this two-part post today and tomorrow, and is independent of the issue of carbon dioxide social benefits versus social costs.
Professor Cullen first determines how much electricity production of other generator types is offset by the presence of wind plants in the grid using a reduced form econometric model based on “observed behavior and current market conditions.” The time frames for production are 15 minute intervals and two hour ahead forecasting by market participants. The market-oriented approach is exemplified by the following quote:
When low marginal cost wind-generated electricity enters the grid, higher marginal cost fossil fuel generators will reduce their output. [emphasis added]
This assumption that the suppliers of generation resources make these decisions is questionable because the nature of the short term operation of an electricity system is more like that of a machine than a market. The electricity system has been described as, “the largest and most complex machine ever made.” Usually the production offset by wind is that which is most easily and quickly varied by the system operator regardless of fuel source or cost. Further, depending on the generation fleet online profile at the time, this can be other emissions free generation, such as hydro or even in some cases nuclear, which admittedly is not easily varied.
This is not to say there is not a wholesale electricity market, but that critical short term electricity system operational considerations are less dependent on decisions by the market participants and more dependent on the system operator matching supply and demand in real time using available online dispatchable generation resources.
So, although the operation of the electricity system is intended to provide the lowest wholesale cost from available choices, the overall reliability of the system is the paramount consideration. Other factors impacting operational decisions include: (1) government mandates to accept wind plant production whenever it occurs; (2) the profile of generation plants in use at the time (this typically varies considerably throughout the 24 hour day, and can be a limited subset, particularly at night); and (3) as already indicated, which of the available online generation plants can most easily be varied to meet the erratic output of wind plants. The Cullen analysis does not take into account the over-riding reliability consideration, as explained at the bottom of page 111.
Finally, the econometric approach cannot comment on wind-induced reliability, or congestion issues that engineering approaches are geared to address.
Having determined the production offsets, the paper suggests that “it is straight forward to calculate emissions offsets by wind.” The emphasis is added because the “straight forward” claim is very questionable. So this review will put both sets of results to the test, and they will be found wanting.
Can opposition to wind plant implementations be encouraged by the results nonetheless? I suggest not without considerable caution for a number of reasons:
- As introduced above, the paper uses an econometric modelling technique involving regression claiming to control for other influencing factors to ultimately lead to a determination of emissions savings from wind. This is a questionable approach in the absence of supporting proof of a clear cause and effect relationship between wind electricity production and claimed emissions and electricity production offsets. An example of such proof will be provided. Other corroboration used by the author will be shown to be not useful.
- The analysis is based on questionable or incomplete data, especially emissions data, both in the approach to calculate the reported emissions savings, and in other reports used to support the “robustness” of this paper’s results.
- The treatment of wind costs is incomplete.
- As acknowledged by Cullen, the results of the sample used, in this case the Texas ERCOT electricity system, are not likely transferrable to other jurisdictions or different levels of wind penetration.
- Other acknowledged shortcomings of the analysis are too important to support a complete understanding of the effect of introducing wind plants into electricity systems.
- The use of questionable claims/opinions do not contribute to the overall dependability and hence usefulness of the study.
Part I of this series addresses the following in more detail:
- Analysis approach
- Robustness claims
A summary of Cullen’s approach is:
Utilizing information on production decisions [by market participants] in 15-minute intervals on the Texas electricity grid, I estimate the response of each generator to exogenous changes in wind power. Realizing that wind power production is not completely random, I control for factors that may drive the incentives for electricity production, which may also be correlated with wind power production. The resulting quasi-experimental residual variation is then used to identify a substitution coefficient for each generator on the grid. Importantly, I show that failing to control for impact that wind has on the dynamic process of electricity production overestimates the production offsets. These production offsets then translate directly into emission offsets using generator emission rates. [emphasis added]
This approach may work if all the factors in determining production and emissions offsets are accounted for, which I suggest is not an easy task, and has not been convincingly and completely done by anyone. Cullen does include a number of factors, but are important ones missed?
One way to test for this is to provide two finely-grained (5 minute intervals or less) time series plots for wind production versus both fossil fuel production offsets and emissions offsets claimed for wind. If these plots clearly show, in timing and relative size, that a very close relationship (or mirror image in the case of negative correlation), then there is merit to the approach. In the absence of a demonstration of this strong cause and effect relationship, the degree of mismatch is an indication of the impact of other factors not modelled.
In the case of the Kaffine, McBee and Lieskovsky study referred to by Cullen, because it employed the same approach “using different data sources”, when such time series plots were provided, there was little indication of a cause and effect relationship between wind production and the residual emissions claimed as a consequence of wind presence.
As a quick test of the possible causal links between wind and fossil fuel electricity production I looked to a chart I had previously prepared for Texas using EIA data. It includes the period analyzed in Cullen’s paper, that is 2005-2007, and is shown in Figure 1. This chart focuses on the changes in electricity production on a yearly basis for fossil fuel plants, wind plants and net imports as an indicator of plausible cause and effect.
Figure 1 shows that in five of the eight years the annual change in wind production is in the same direction (both up or down) as that for fossil fuel, which suggests that wind is not the major factor in offsetting fossil fuel generation. However, for five of these years the change in net imports is in the opposite direction as changes in fossil fuel production. Note the relative sizes as well. This suggests that imports are more likely a factor than wind in offsetting fossil fuel electricity production.
Do not be confused by the use of the term net imports, in the context of a net exporter for the time period in Cullen’s analysis. Net imports are used here because imports are an additive generation source and are thus shown as positive in the chart. When net import changes are positive, year over year, this means there was an increase in imports relative to exports.
This test may not be conclusive, but it reinforces that further verification as described above would be appropriate.
In the absence of such corroboration, the results remain suspect because the sophistication of the approach is not a guarantee of accuracy. See more comment under the Robustness Claim (below) and Interstate Trade in Electricity sections in Part II.
There is interesting information bearing on the impact of cycling fossil fuel plants, whether for just “normal” frequency regulation (load variation only) or the additional requirement of balancing wind.  On a short term basis, such as minutes (or less), both have the same type of system impact. This is referred to in a KEMA  report, “Emissions Comparison for a 20 MW Flywheel-based Frequency Regulation Power Plant” in which a reference is made to another KEMA report on the impact of such cycling on the fuel consumption and hence emissions of fossil fuel plants. Attempts to get a copy of the referenced report have not been successful, but Dr. Kees lePair, in the Netherlands, claims to have had access to it and describes its findings in his paper “Wind turbines increase fossil fuel consumption & CO2 emission” as follows:
Recently we received some information concerning a fuel flow recording of a coal fired generator during cycling. The generator running stationary for some time at 100% of its optimal capacity reduced its output to 80% and up again to 100%. The whole cycle took place in one hour. The total fuel consumption during that period was 1,2% more than it would have been had the machine continued running at 100%. It was suggested that for a CCGT this outcome should have been 1%.
Given the combined effect of: (1) the more frequent cycling of fossil fuel plants than KEMA observed, whether normal frequency regulation operations or balancing wind plants, and (2) an overall reduced electricity output, and therefore less efficient operation due to periods of part loading in the fossil fuel plants as a result, it is difficult to escape the expectation of very little emissions savings at best over a normal steady operation of the fossil fuel plants meeting the demand alone. In other words, wind presence likely increases emissions overall.
In the first paragraph in the “Robustness” section of Cullen’s paper he expresses some concern about using averages of emission rates and acknowledges emissions effects missed, but counters this with the claim that as the number of fossil fuel plants supporting this cycling requirement increases, the changed output of each would be eased thus reducing the fuel and emissions impacts. This misses the important consideration that the frequency of such cycling is at least, if not more than, as important as the extent of the changes required. Further, grid topology could also restrict wind’s impact to subsets of fossil fuel plants.
In the “Robustness” section the paper looks to the Katzenstein and Apt analysis “Air Emissions Due to Wind and Solar Power” for confirmation of results. Most readers appear to miss the many caveats that Katzenstein and Apt correctly identify. For example:
As discussed in the Supporting Information, the emission and heat rate data we obtained for the gas turbines did not cover all combinations of power and ramp rate. We therefore further constrain the model to operate only in regions of the power-ramp rate space for which we have data.” [emphasis and link added]
and caution that we have made no attempt to ensure the stability of an electrical grid. Grid dynamic response may somewhat change our results. [it is suggested that “somewhat” is an understatement]
Realistically, displaced generators will differ from the generators providing fill-in power and would produce different results.
With respect to the last quote above, there is, or will be, a trend to introduce different types of generator plants (less expensive and more flexible) to balance wind as wind penetration increases. One example would be the increased use of gas turbine (aka GT or SCGT) plants versus combined cycle gas plants (CCGT). The gas turbine plants produce about 50% more emissions per MWh than combined cycle gas plants, the latter being designed to operate in steady state base load or intermediate electricity production roles. This is a major and often overlooked factor that contributes to reducing wind emissions offsets. See additional comments on this in the Questionable Data section in Part II.
Further, the impact of low operating cost of wind plants on wholesale markets, in part due to subsidization, makes more expensive operating cost, but more reliable, generation plant investments less attractive, thus putting at risk long range capacity needs. This is a serious matter for longer term electricity system reliability.
This is not to say that all wind costs are as indicated by wholesale market bidding, which is based only on the cost at the wind plant site, because there are substantial additional electricity systems costs which are incurred solely because of wind’s presence. This is discussed further in Part II.
From the Katzenstein and Apt paper Supporting Information addendum:
Therefore, the results seen in Table 1 of the main paper, obtained from using the full time series of the 5 data sets (see Table S6), estimates only the emission reductions for the conditions that existed during the periods when the data were collected. Ideally, a significant number of high time-resolution independent power plant outputs would be used in our simulations. However we did not have access to such a data set, only to the 5 data sets described. [emphasis added]
The wind data sets were for the relatively short periods of 15, 84, 240 and 370 hours. The fifth data set was for solar PV. This speaks to the limited data impact on conclusive results.
In summary, the Katzenstein and Apt paper does not contribute to robustness for the Cullen paper, due to the limitations of both.
Part I has shown that Cullen’s approach and robustness claims are questionable. Part II will look in more detail at the reliability of the available data, the interstate trade in electricity considerations, and discuss briefly some of Cullen’s acknowledged caveats and some other claims made.
 There is an earlier version which may be accessed at http://www.u.arizona.edu/~jcullen/Documents/measuringwind.pdf , but no attempt has been made to confirm that it is an identical document.
 EIA http://www.eia.gov/electricity/data/state/ Go to first spreadsheet entitled “Net Generation by State by Type of Producer by Energy Source (EIA-906, EIA-920, and EIA-923)” for Wind data, http://www.eia.gov/electricity/state/texas/ Table 10 for Net Interstate Trade and Table 4 for fossil fuel data.
 The short term (minutes or less) variation of load and wind in combination produces a greater range of variance than either individually, with a bias towards greater instances of higher variance. An analysis of the Bonneville Power Administration (BPA) in the US northwest electricity production by fuel source at 5 minute intervals shows this. Note that this assumes an arithmetic summation of all wind production, and grid restrictions might exacerbate this experience on a more localized basis.
Where Wind Studies Go Wrong: Cullen in AEJ (Part II)
“The level of emissions savings provided by wind plants has never been conclusively determined, taking into account all the factors.”
Part I yesterday questioned the analysis and robustness of Joseph Cullen’s study, “Measuring the Environmental Benefits of Wind-Generated Electricity”.  Part II completes the commentary on this paper, covering:
- Questionable data, which seriously inhibits any analysis of wind performance
- Interstate trade in electricity, an often overlooked, but important, consideration in understanding impacts on emissions
- A summary of the acknowledged shortcomings of this paper
- Questionable opinions/claims made
The level of emissions savings provided by wind plants has never been conclusively determined, taking into account all the factors. Further, there is no published accurate, minute-by-minute, actual fuel consumption or emissions by individual plant, especially for systems with notable levels of wind present. Note the limitations in the Katzenstein and Apt paper looked to by Cullen for corroboration as discussed in Part I.
In general, government reported emissions are estimates based on calculations using assumptions and relatively simple algorithms. In some cases, actual measurements are taken but are no better than those calculated as reported by the International Energy Agency (see page 35).
Commercial instrumentation is available for monitoring CO2 concentration and flue gas volume flows. Given the limitations of such instrumentation, the accuracy of directly measured CO2 release is probably no better than that derived by indirect calculation. [emphasis added]
A report by The Sustainable Energy Authority in Ireland, “Renewable Energy in Ireland”, in Appendix 1 also refreshingly recognizes the limitations to existing reporting methods.
The assumption underpinning this approach is that the renewable plant is displacing the last plants to be dispatched to meet electricity demand, i.e. the marginal oil and gas plants. There are clear limitations in this analysis but it does provide useful indicative results.” [emphasis added for “indicative”, which is taken to mean “suggestive”]
“The limitations and caveats associated with this methodology include that it ignores any plant used to meet the associated reserve requirements of renewables. These open cycle plants will typically have lower efficiency and generate increased CO2 and NOx emissions compared with CCGT and these emissions should be incorporated into the analysis. The purpose of presenting a simplified analysis here is to provide initial insights into the amount of fossil fuels that are displaced by renewables and the amount of emissions thereby avoided. [emphasis added]
The issue raised in the last quote speaks to the comments made in the Robustness section in Part I.
The above comments point out some of the typical shortcomings of many current approaches in determining reported emissions offsets for wind. At best, such results are useful only as some indication and for rough comparison purposes, for example between jurisdictions and time periods, and not reliable for absolute levels.
The Cullen article admits that the modelling approach used, “relies only on publicly available generator output and characteristics”. Emphasis has been added to the quote because there is no adequate, publicly available information on the constant cycling required of other generation plants mirroring wind plants’ highly random output on a short-term basis, as indicated in Katzenstein and Apt’s paper in Part I.
Cullen somewhat distances his results from the EPA system CEMS on the basis that CEMS reporting includes less than two-thirds of the generators in the ERCOT system, a notable comment in itself.
As a robustness check, I estimate the same model with hourly emissions data from the EPA’s Continuous Emissions Monitoring System (CEMS) as the dependent variable. Using CEMS data may be able to account for the changes in the emissions rate due to efficiency changes, though it may exacerbate ramping effects.
The latter part of this quote needs elaboration. Cullen shows that using the CEMS data in his model results in 4% lower CO2 emissions offsets for wind. He concludes that this indicates relative robustness, but the CEMS data “may” exacerbate ramping effects. This implies that Cullen has in fact captured the ramping effects, which is very questionable as already described.
However, CEMS reporting is subject to question as indicated above. Also note that the CEMS data is hourly based, which likely masks ramping effects on much shorter time intervals in which electricity system balancing must operate to ensure system reliability. In summary the CEMS information more likely understates the ramping effect.
So questionable or incomplete data is a problem in the determination of complete and accurate results, and any corroboration claimed by Cullen is questionable.
Interstate Trade in Electricity
This is a factor that is almost always overlooked in analyses of wind performance, and is not taken fully into account in the modelling here. The general reason for this is that electricity exports to or imports from another jurisdiction are a somewhat complicated matter, and unfortunately often are taken to be relatively inconsequential, which they usually are not.
When Cullen is talking about electricity imports, it is presumed he is talking about net interstate trade, as opposed to import/export of electricity in connection with another country. For simplicity here, the terms “interstate trade” and “exports/imports” will be used to refer to interstate trade only. Further it is important to be clear whether or not any reference to this is a net number of exports/imports as is often the case in reported values.
Cullen also says that he observes the flows of electricity over connection lines in neighboring grids in 15 minute intervals and claims that less than 1 percent of daily generation is exchanged with other grids, while wind accounts for approximately 2%, which allows him to restrict his analysis to within the Texas system. However, this does not agree with EIA reports,  as summarized in Table 1.
Table 1 – Wind Production and Net Interstate Trade as Percent of Total Texas Electricity Production.
Note that total wind production is at the same level as net interstate trade for two of the three years that Cullen analyzed, but the net of the interstate trade and could conceal larger amounts of export and import levels over the same period.
Further, Cullen talks in terms of imports, but in the three years analyzed, Texas was a net exporter of electricity. Note the balancing of Supply and Disposition in the reference shown for Table 1. Some clarification of this by Cullen would have been helpful.
In summary, notwithstanding the relative isolation of the Texas electricity system, interstate trade in electricity cannot be ignored in the analysis, and exports/imports even on a net basis could just as easily account for much of the reductions in fossil fuel plant emissions as wind.
To further examine misunderstandings in connection with inter-jurisdiction trade in electricity, in footnote 30 for imports, Cullen suggests that if it was assumed that the emissions offset profile of imports to be the same as in the models, this would change the results found.
It is preferable to assume imports carry no emissions, as it would be very difficult to identify the specific source of the electricity generation profile behind the exported electricity. For the purposes of simplicity in explaining this, assume that such distinction can be made in a couple of simple cases.
The exporting jurisdiction is exporting electricity associated with emissions. For the importing jurisdiction to also be charged with these emissions would be double accounting, unless the exporter took a balancing credit. Imagine the complex negotiation associated with this arrangement.
In the case of exporting electricity from non-emissions producing generation there is no need to associate emissions with either the export or import as well. However there is an example where this is not done. Denmark reports emissions in two ways: (1) as produced, and (2) after taking credit to reduce its actual emissions based on the amount of exported wind production.
The latter view is often cited in error. See Peeling Away the Onion of Danish Wind for more details. Here as above, this works if the receiving jurisdiction takes a balancing increase in reported emissions, which is unlikely, resulting in a double accounting for emissions reductions, an undesirable outcome.
Admittedly inter-jurisdiction trade in electricity is somewhat complicated, and the above descriptions are simplifications to illustrate the need to view associated emissions as staying within the electricity generating jurisdiction. Imports/exports from and to another jurisdiction should be treated as emissions free.
Perhaps the most important matter is that in most cases, even in Texas, imports and exports of electricity must be fully taken into account when analyzing the emissions impact of wind presence.
The paper contains appropriate caveats including:
- Limitations with respect to transferring results to different wind penetrations or electricity systems.
- No consideration is given to electricity system reliability.
- It is not a comprehensive cost benefit analysis of wind power.
- It does not address the different nature of future generation plant type investments induced by wind.
- Note 32 says the paper does not “disentangle how the variability of wind power affects the emissions offset.”
These properly acknowledged limitations reduce the value of the paper in providing useful insights and reliable conclusions about the effects of deployment of wind power.
There are a number these, which further reduce the value of this paper.
The statement, “In fact, nearly all costs associated with wind power production are incurred during the construction and installation phase of a wind farm.” is not correct. Substantial additional costs are incurred by the presence of wind in (1) otherwise not needed, dispatchable capacity to balance wind’s persistently, erratic behavior within short periods of time (minutes or less) and unreliability on a longer term basis of hours and days, and (2) in substantial increases to the grid unique to wind to gather wind’s dispersed generation, transmit it to typically distant demand centers and support demand management in distribution systems. See the series on “Wind Consequences” for more information.
A modern 1 MW (not 1 MWh) wind turbine does not require only “roughly $1 million” to install. Overnight implementation costs are over twice this amount according to the EIA.
Cullen assumes a Wind turbine life of 20 years and that any change in operating efficiency over its lifetime is negligible. This is contrary to experience that shows substantial reductions in performance measured by load factor (aka capacity factor). Figure 2 shows experience in Denmark and the UK. 
Figure 2 – Performance Degradation of Wind Turbines in Denmark and the UK
The values shown here are weighted by capacity, because this better captures the effect of the most numerous wind turbine sizes, and produces more typical results than simple averaging. The years with no values are because of little or no experience. Outages due to mechanical failure are included in these statistics.
Most of today’s wind turbine installations have occurred since 2000. These are typically 1-3 MW and much larger than their predecessors. These larger wind turbines have a 100 ton  blade assembly and nacelle enclosing the generator on top of a 200 foot, or more, tower. They are reported to be the largest rotating structures in the world. A possible explanation of Denmark’s slower degradation experience may be because most were installed before 2000 and the majority are of a much smaller size.
There are many considerations behind these numbers, but a strong case is made for concern about considerably shorter than generally expected life times for wind turbines, as indicated by the quote from this paper:
With such low levels of performance it seems very unlikely that large wind farms will continue in operation beyond 10 years of age, with a strong likelihood of re-powering at that point. The consequence is that large scale reliance upon wind power seems likely to involve a regular – and costly – commitment to upgrading major components of the wind turbines.
There are other reports on frequent, major component failures requiring substantial costs in the order those for the initial implementation. 
On page 112, Cullen refers to a paper by Holland and Mansur, which describes how real time retail pricing would shape demand by reducing peaks and shifting load to low cost periods at night. Holland and Mansur explain that this can have an impact on emissions, but whether the impact is positive or negative depends on the generation plant profile of the jurisdiction. Cullen claims that wind plants likewise reshape demand, which is not obvious at all. Apart from the fact that there is no mention by Cullen of the necessary attendant real-time retail pricing, wind usually has higher production at night, and it thus tends to shape low cost production base load generation (not demand) in this period. Further he states that this re-shaping of demand necessarily leads to emissions offsets, which is different from Holland and Mansur’s conclusions which allows for the possibility of increased emissions as well.
As described above in the Analysis Approach section, a major effect of wind is its impact on short term residual demand variances, a totally different type of demand shaping. This shapes the residual demand in a non-beneficial way and arguably increases emissions overall.
Cullen states, “However, for both economic and environmental reasons, hydro facilities are unlikely to spill water over dams without generating electricity.” This is clearly an inappropriate assumption and demonstrates his emphasis on market participants determining electricity system operations. The Bonneville Power Administration (BPA) in the Pacific Northwest provides an instructive case study of system operational issues and associated contortions required here and here.
Another related comment by Cullen is, “Both nuclear and aggregate hydropower production will be largely unaffected by the roll out of wind farms.” The use of “largely” is acknowledged, but the statement can be read to suggest non-problematic impacts. The BPA experience above speaks to the hydro aspects. Admittedly nuclear is an unlikely form of electricity generation to be offset by wind, but it does happen as discussed here.
A final very questionable claim is, “First, technology advancements in wind turbines have reduced the cost of wind power by 80 percent over the past 30 years (Wiser and Bolinger 2007).” I could not find confirmation of this claim in the referenced paper. A chart on page 21 does show project costs per kW reducing by about 65% between 1982 to 2000 and then increasing thereafter. This has a related comment in footnote 35, ” Limited sample size early on – particularly in the 1980s – makes it difficult to pin down this number with a high degree of confidence.”
Further to claim technology advancements have been the cause is questionable. The cost per kW of a wind turbine has been largely influenced by simple mechanical considerations, primarily the size of the blades and height of the tower, both of which have increased dramatically over this period.
Given the very large portion of national wealth (multiples of $trillions) necessary for the contemplated extensive deployment of wind plants, and the associated longer term risks to electricity system viability and reliability, we simply have to do better at complete and conclusive analysis of the impact of wind plants with much improved public availability of operational data on generation plants, including real time fuel consumption and accurate emissions. Fuel consumption may be the only realistic way to assess emissions.
It is questionable that sophisticated econometric modelling is appropriate for this task.
 As indicated in Part I, there is an earlier version which may be accessed at http://www.u.arizona.edu/~jcullen/Documents/measuringwind.pdf , but no attempt has been made to confirm that it is an identical document.
 Hughes, Gordon (2012). “The Performance of Wind Farms in the United Kingdom and Denmark” http://www.ref.org.uk/attachments/article/280/ref.hughes.19.12.12.pdf Chart is based on calculations from Figure 2.
 This is not widely reported, and some links to sites previously dealing with this topic appear to have removed the documents in question. Here are some currently available reports relating to this matter.