Wind energy’s price suppression effects (Debating wind power cost estimates – 6)

[Series header: On the Morning of October 15 the Institute for Energy Research in Washington DC released a report I’d written about the federal government's wind power cost estimates. (Links available here.) Later that day Michael Goggin of the American Wind Energy Association, the lobbying organization in Washington DC that represents the wind energy industry, posted a response on the AWEA website: “Fact check: Fossil-funded think tank strikes out on cost of wind.” I’m considering points made by the AWEA response in a series of posts.]

Goggin objects to my report’s emphasis on the high cost of wind energy. He said, “The reality is that wind energy is driving electricity prices down, thanks to large recent reductions in its cost.” I agree with Goggin, as I said earlier in this series of replies, at least on price suppression: “Wind power is responsible from bringing down average prices in regional power markets, a consequence of subsidizing entry of generation with high capital costs but low marginal operating costs.”

But the effect of wind energy on prices is only obviously negative in the short run. Longer term the cost of energy could rise. More importantly, the price suppression effect is only tangentially related to the overall benefits and costs of wind power policy and so of only modest policy relevance.

The basic short-run “price suppression” effect is explained various places–here is a bit from a short report produced by the staff of the Public Utilities Commission of Ohio, “Renewable resources and wholesale price suppression” (August 2013):

Price suppression is a widely recognized phenomenon by which renewable resources produce lower wholesale market clearing prices. The economic theory that drives price suppression is actually quite simple. Renewable resources such as solar and wind are essentially zero marginal cost generators, as their “fuel” costs (sunlight and wind) are free. As such, they will always be dispatched first by the grid operator, thereby displacing units with higher operating costs. This results in lower wholesale market clearing prices than would have been experienced in the absence of the renewable resources.

A simple graphical representation appears below. The new renewable resources (depicted by the red line) are added to the dispatch stack, shifting the supply curve out and to the right. This results in a lower cost unit setting the market clearing price, shifting the equilibrium price down from Po to P1.

PUCO, Renewable Resources and Wholesale Price Suppression,” August 2013.

The above analysis, so far as it goes, adequately shows the simple short-run impact of adding low marginal cost resources to a supply curve. The marginal cost of producing wind energy isn’t zero–wind turbines experience wear from operation and non-zero maintenance costs. But the marginal costs are low relative to most other power plants and the short-run impact on spot prices is to push prices down. In the simulations for Ohio analyzed by the PUCO staff, the effect is a price suppression of between $0.05 and $0.20 per MWh (or, to put it in residential consumer terms, a reduction in energy cost of 0.02 cents per kwh).

But, as the staff of the Public Utilities Commission explain in their report, observing a tiny tiny price suppression effect doesn’t indicate anything about overall costs and benefits or about least-cost capacity expansion. The above analysis is a short-run assessment that ignores longer term effects on investments and retirement of assets. A more complete assessment, they said, would need “to consider additional variables such as capital and capacity costs, renewable energy credit (REC) prices, and transmission upgrade expenses.”

And that is among the problems with Goggin’s simple-minded trumpeting of a price suppression effect as some sort of renewable energy triumph: it ignores the future consequences of the policy. Other things being equal, as intermittent low-marginal-cost resources are added to a power system, less-flexible medium-low marginal cost baseload power plants tend to be most disadvantaged and most likely to be retired. At the same time, the resulting increased need for flexible, dispatchable resources will tend to support investment in responsive natural gas generators that have lower capital costs but medium to high marginal costs.

These changes to the generation portfolio in a market will also shift the shape of the supply curve. It is an empirical question, or will be in five or ten years when energy markets have finished adjusting to the 2018-2013 wind energy construction boom in the United States and data is available, whether the overall effect has been to reduce or increase average prices to consumers.

But there is at least on more point: public policy analysis ought to involve a careful counting of projected benefits and costs. It is hardly surprising that subsidizing entry of production capacity would tend to drive down market prices in the short run, but that says nothing about either the short-run or long-run overall benefits and costs of the subsidy policy. The high capital costs of wind energy are one big signal that the steel, concrete, rare earth magnets, other component parts and manufacturing expertise that are drawn into wind energy production all have valuable potential other uses in the economy. We forgo these other potential contributions when policy steers these resource into electric power generation.

Are consumers better off when public policy pulls some of these resources from the manufacture of other goods and services and pushes these resources into electric energy supply? Maybe yes and maybe no, but the price suppression effect is mostly about the division of the spoils of wind power policy, and has little to do with the overall benefits and costs of the policy.

PJM region could handle substantially more renewable generation, study says

PJM Interconnection has been studying, with the help of GE Energy Consulting and other groups, the consequences of adding significantly more wind energy and solar energy to its transmission grid. The “headline result” of a preliminary report, presented to PJM stakeholders recently, is that the system could handle renewable power generation capacity at a 30 percent penetration rate in 2026.

Here is how EnergyWire summarized the preliminary results (may be gated):

The eastern Great Lakes and mid-Atlantic region could rely on wind and solar power for as much as 30 percent of their generation capacity without threatening electricity delivery with net benefits even after additional transmission lines and reserve resources are added, according to a preliminary study released by the PJM Interconnection, the region’s grid operator.

The study, by GE Energy Consulting, investigates several scenarios for additions of wind and solar generation to the PJM grid, which extends from New Jersey to northern Illinois. It calculates the amount of new transmission lines needed to deliver the renewable energy and the required backup generation to support the variable wind and solar power.

The main impacts it reports are lower emissions of pollutants and greenhouse gases; no power outages and minimal curtailment of renewable energy; lower systemwide energy production costs; and lower wholesale customer power costs with the additional wind and solar resources.

“Even at 30 percent penetration, results indicate that the PJM system can handle the additional renewable integration with sufficient reserves and transmission build out,” GE said.

GE Energy Consulting is one corporate unit in the General Electric family, other corporate units make and sell generation equipment including wind turbines, solar pv products, natural gas turbines, etc. We can probably assume that GE Energy Consulting had access to good information in preparing their analysis.

Scanning through the 149-slide presentation reveals a bit about what GE Energy Consulting understands concerning intermittent renewable generation. For example, slides 49-55 discussed the transmission additions needed under the various scenarios studied. Slide 15 summarized the added transmission costs, which ranged from $3.70 to $13.7 per MWh depending on scenario.

On the question of whether adding intermittent renewable generation increases reserves requirements, the report concludes at slide 67, “The study identified a need for an increase in the regulation requirement even in the lower wind penetration scenario (2% BAU), and the requirement would have noticeable increases for higher penetration levels.” Regulation, as the term is used in power systems, refers to a fast-responding reserves service that dispatchable generators can provide to the grid.

Power plant cycling costs are discussed at slides 78-93; the report indicates that adding renewable power results in more cycling operations for dispatchable power plants, higher cycling costs for dispatchable power plants, and less time spent operating in more efficient stable-output baseload conditions. Cost estimates for cycling range from $0 to as much as $21.90 per MWh of renewable output, depending on the scenario studied and the type of unit forced into additional cycling.

Power plant cycling emissions are discussed at slides 94-101; the report indicates that added cycling of fossil fuel plants does offset some of the emission reductions that might otherwise be expected from using wind energy or solar energy, but the effect is pretty small.

The report estimates the overall value of the renewable energy delivered to the system at about $50 per MWh.

The GE Energy Consulting analysis is interesting, in part, because of how their projections relate to my recently released report on wind energy cost estimates. I observed, among other things, that in addition to the costs of wind power capacity to  project developers, there were other costs to be considered when evaluating wind energy in a policy context. Among the factors noted: transmission additions, grid-integration costs (mostly added reserves), some partial offsetting of renewable’s emission benefits due to increased cycling of dispatchable power plants, and added cycling costs imposed on the owners of these dispatchable units.

Michael Goggin of the American Wind Energy Association attacked my report on Into the Wind, the trade association’s blog, for “rely[ing] on obsolete data” and “regurgitat[ing] anti-wind myths that have already been debunked.” (I’ve responded to Goggin in a series of posts.)

I am now looking forward to Goggin’s attack on GE Energy Consulting for perpetuating these anti-wind myths.

NOTE: Here is Goggin’s actual reaction to the GE report, where instead of accusing GE Energy Consulting of failing to understand how the power grid operates, he chooses to accentuate the positive: “Independent grid operator study confirms wind power’s economic, environmental value.” (I guess it would have been awkward to complain too much about the report since GE Energy is an AWEA member.)

Debating wind power cost estimates – 5

[Series header: On the Morning of October 15 the Institute for Energy Research in Washington DC released a report I’d written about the federal government's wind power cost estimates. (Links available here.) Later that day Michael Goggin of the American Wind Energy Association, the lobbying organization in Washington DC that represents the wind energy industry, posted a response on the AWEA website: “Fact check: Fossil-funded think tank strikes out on cost of wind.” I’m considering points made by the AWEA response in a series of posts.]

In the final section of Goggin’s detailed criticisms of my report he takes on my claims with respect to various additional costs associated with the addition of wind power to the grid, including grid integration costs, indirect pollution effects, transmission expenses, and negative prices. He writes:

After starting with a baseline wind cost that is 100% too high, IER compounds the error by claiming that the actual costs of wind are even higher based on obsolete data and a flawed understanding of how the power system works.

IER incorrectly alleges that wind energy imposes large “integration costs” on the power system. In reality, it is far more costly to integrate the unexpected and instantaneous failures of large fossil and nuclear power plants than to accommodate the gradual and predictable changes in wind energy output.

I’m note sure just where the report “alleges that wind energy imposes large ‘integration costs’ on the power system.” All that my report does is (1) observe that grid integration costs are not included in NREL levelized cost of energy estimates so a fuller consideration of costs much include them, (2) summarize the discussion of the topic in the Lawrence Berkeley National Lab’s 2012 Wind Technologies Market Report [WTMR], and (3) highlight factors that tend to increase or decrease those costs.

Here is the core of my wind integration cost claim: “The [WTMR] reported a range of cost estimates from wind power integration studies, with all studies but one falling below $12 per MWh and some studies below $5 per MWh.” From this remark somehow Goggin claims I allege the costs are large.

Goggin then cherry-picks a few examples of low wind integration cost estimates. But each of these examples is included in the far more comprehensive WTMR study produced by the Berkeley Lab. You can find his 3 examples, and 22 others, in figure 37 of the 2012 WTMR, p. 63. The American Wind Energy Association may not like the answers, but again it seems that Goggin’s complaint is with the Berkeley Lab research and not my report.

Goggin again:

IER’s report falsely alleges that wind energy’s pollution reductions are significantly reduced because of this incremental need to operate other power plants more flexibly. IER picked a bad time to once again try to push that myth, as last month a comprehensive report used real-world emissions data from every power plant in the Western U.S. to confirm that wind energy produces the expected pollution reductions. … IER’s claim to the contrary is based on a single report that has been thoroughly debunked for getting the wrong answer because its authors failed to understand how the power system works. [Link in source.]

Goggin discusses issues raised in section 3.3 of my report on additional cycling of baseload units and section 3.4 of my report on environmental costs. I cite a handful of references in these two sections and Goggin doesn’t include links. As best as I can tell by “single report” Goggin is referencing the Katzenstein and Apt article published in the journal Environmental Science & Technology, “Air Emissions Due to Wind and Solar Power,” and the “thorough[] debunking” is the comment on that piece by Mills, Wiser, Milligan and O’Malley.

On this point, while Goggin exaggerates his point in cartoonish fashion, he raises a good point. The nub of the issue is that the Katzenstein and Apt article use a very simplified case to examine the relationship between renewable power intermittency and emissions from dispatchable generators, and the simplified case yields a much higher reduction in emission benefits than renewable power intermittency actually yields when connected to large scale power grids. That is to say, as Katzenstein and Apt acknowledge and Mills et al. emphasize in their comment, the Katzenstein and Apt result is essentially an estimate of the possible upper bound of the effect. Mills et al. make clear that in actual power grids the reduction in emission benefits, while still present, is likely much smaller in practice. In short, the study I emphasize was not the best choice to show the indirect emission effects of renewable energy intermittency in large scale power grids. (Having met Jay Apt once or twice, I’d be very reluctant to accuse him, as Goggin does, of failing to understand how the power grid works.)

Goggin objects to my referencing transmission costs as another factor to be considered as associated with wind power, since “upgrades to the nation’s obsolete and congested electric grid are needed anyway regardless of the addition of wind energy” and transmission upgrades will more than pay for themselves by broadening access to low cost generation. I’m sure Goggin understands enough about how the power grid works to understand that “upgrades to the … grid … needed anyway regardless of the addition of wind energy” will be somewhat different from “upgrades to the … grid … needed” because of the addition of wind energy. Perhaps amusingly, the Western Wind and Solar Integration Study Goggin cites against me on the emissions point tends to support my point on transmission costs: in Phase 1 of the study they assume significant enhancement of the grid in the Western U.S. to accommodate assumed addition of large amounts of wind and solar power.

If modelling assumptions don’t convince Goggin, then surely he has heard of the $6.8 billion CREZ grid upgrades in Texas that were designed accommodate existing and projected wind power production. Most of the CREZ upgrades would not have been useful in the absence of wind power and certainly the ERCOT grid would not have been expanded to overlap the Southwest Power Pool grid footprint in the Texas Panhandle and South Plains area in the absence of a high-quality wind power resources in the region. Transmission upgrades can enhance competition, like Goggin points out, but had ERCOT wanted transmission upgrades primarily to enhance competition then the money would have been spent much differently. The grid upgrade plans and the associated expenses were largely driven by the fact that high-quality wind power resources are location dependent, and those locations are distant from the primary areas of power demand in the state.

Obviously the selection of power plant location is important for any kind of generator, and good locations will always be constrained (usual main factors: access to fuel, access to water for cooling, access to consumers, and cost of land). But for coal, nuclear, and natural gas it is possible to deliver the energy resource to locations nearer ultimate consumers. In the cases of wind, hydropower, and geothermal energy the resource locations are determined primarily by nature (and not with net-system-cost minimization in mind).

Next: Two issues remain, both concerning the effects of wind power on regional power market prices. I’ll look at the price suppression effects of adding wind to the grid in my next post in this series and then I’ll take another look at negative power market prices.

Debating wind power cost estimates – 4

[Series header: On the Morning of October 15 the Institute for Energy Research in Washington DC released a report I’d written about the federal government's wind power cost estimates. (Links available here.) Later that day Michael Goggin of the American Wind Energy Association, the lobbying organization in Washington DC that represents the wind energy industry, posted a response on the AWEA website: “Fact check: Fossil-funded think tank strikes out on cost of wind.” I’m considering points made by the AWEA response in a series of posts.]

Next in his response Goggin moves into a more detailed version of his claim my report “relies on old and theoretical data for the cost of wind, even though it had access to more recent real-world data.”

As I mentioned in an earlier post, I primarily draw on the Lawrence Berkeley National Lab’s 2012 Wind Technologies Market Report (WTMR), published in August 2013, and the National Renewable Energy Lab’s 2011 Cost of Wind Energy Review (CWER), published in March 2013. These two reports are the most recent publications in the federal government’s two long-standing research efforts examining the cost of wind energy. If this work isn’t current enough for Goggin, his complaint is with the national labs and not me.

The WTMR summarizes “real-world data,” while the CWER presents Levelized Cost of Energy (LCOE) estimates for wind power. The NREL’s LCOE estimate relies on data from the Berkeley Lab’s WTMR and is typically published a few months later. Since the Berkeley Lab’s 2012 report was published a little over two months ago, the NREL LCOE estimate update for 2012 likely won’t emerge for another few months.

My report focuses on these two recent government publications because they are the latest summaries from the two most thorough and complete research efforts on the developer’s cost of wind energy in the U.S., and because they are the source of the most frequently cited information on wind energy costs.

In the following I reply to remarks Goggin makes in the first half of his more detailed comments.

Continue reading

MasterResource–$0.11/kWh: Why Wind Is More Expensive than Advertised

At the MasterResource blog, “$0.11/kWh: Why Wind Is More Expensive than Advertised,” a quick summary of my report for the Institute for Energy Research, “Assessing Wind Power Cost Estimates.”

And be sure to notice in the comments on that blog post: remarks from the American Wind Energy Association.

Debating wind power cost estimates – 3

[Series header: On the Morning of October 15 the Institute for Energy Research in Washington DC released a report I’d written about wind power cost estimates sponsored by the federal government. (Links available here.) Later that day Michael Goggin of the American Wind Energy Association, the lobbying organization in Washington DC that represents the wind energy industry, posted a response on the AWEA website: “Fact check: Fossil-funded think tank strikes out on cost of wind.” I’m considering points made by the AWEA response in a series of posts.]

The AWEA response to my report includes the retort, “IER is also incorrect in alleging policy support for wind energy is large or unusual.” (Link in source.)

Actually, no claim in my report suggests policy support for wind is large relative to other energy resources–I don’t discuss subsidies or policy supports for other energy sources. I didn’t intend to allege a relative subsidy size claim. But if Goggin is interested in my view, it is: Unfortunately, policy supports for politically-favored energy sources are not at all unusual, and they tend to reduce overall economic performance, and we’d be better off if we gave up on trying to direct energy markets from Washington DC.

We can’t reach back and undo all of the damage from bad energy policies of the past, but we ought to fix the energy policy we have now. And by “fix” I mean cut energy production subsidies, purchase mandates, favorable tax treatments, regulatory limits on competing energy resources, and otherwise minimize the role of political influence in the choices of energy producers and consumers.

Cut them all down: renewable subsidies, fossil-fuel subsidies, and nuclear subsidies. Sure, do something about pollution, and I’m not in principle against government-sponsored research, but various energy production subsidies and other policy supports tend to benefit a few at the expense of the rest of us.

What my report does claim is the PTC-subsidy for wind power imposes costs on non-wind participants in power markets. Without the PTC, we’d have a lot fewer wind turbines connected to the grid; the wind turbines that did get built would not bid into markets at negative prices, and with fewer wind turbines installed the resulting modest displacement of non-wind power might even be a net economic benefit.

Part of the problem is the PTC subsidizes output at the margin and so directly distorts prices and the generation mix in regional power markets. The alternative Investment Tax Credit subsidy sometimes available to wind power developers, on the other hand, is inframarginal and a bit less distorting: excessive amounts of wind are built, but ITC-subsidized wind power faces no special incentive to run at negative prices. (In economics terms, the ITC is more like a lump-sum transfer while the PTC is a per-unit production subsidy. A per-unit production subsidy is typically seen as more distortionary than a lump-sum transfer.) Generally, when wind power runs at negative prices, it suggests that non-wind baseload power plants are being pushed into a costly pattern of cycling off and back on. These cycling costs, as well as the modest wear-and-tear on the wind turbines operating when their output has negative value, are excess costs caused by the PTC subsidy.

Next: So far I’ve been responding to the introduction of the AWEA/Goggin response. The rest of the response goes into a little more detail on certain points–I’ll respond in a little more detail as seems appropriate.

Debating wind power cost estimates – 2

[Series header: On the Morning of October 15 the Institute for Energy Research in Washington DC released a report I’d written about wind power cost estimates sponsored by the federal government. (Links available here.) Later that day Michael Goggin of the American Wind Energy Association, the lobbying organization in Washington DC that represents the wind energy industry, posted a response on the AWEA website: “Fact check: Fossil-funded think tank strikes out on cost of wind.” I’m considering points made by the AWEA response in a series of posts.]

Goggin complains I am relying on obsolete data and government estimates in my report instead of “price data from signed contracts.” He wrote:

The reality is that wind energy is driving electricity prices down, thanks to large recent reductions in its cost. Contracts that utilities signed to purchase wind energy, which were approved by state regulators and filed with the Federal Energy Regulatory Commission, document that the average purchase price for wind energy was $40 per MWh in 2011 and 2012.

While IER tries to hide behind old data and theoretical estimates, it cannot escape from the real-world data proving that utilities are signing low-cost contracts to purchase wind power. It is strange that an organization that claims to support free-market price signals would use government estimates instead of price data from signed contracts.

Wind energy’s costs have fallen by more than 40 percent over the last four years. These cost declines have been driven by technological improvements as well as the development of a domestic wind-turbine manufacturing sector that now builds over 70 percent of wind turbine value in the United States. [Emphasis in original.]

It is true that wind energy is driving electric prices down, but it has little to do with the reduction in capital cost and more to do with the effect of adding low marginal cost wind power in regional power markets. Whether these are efficient prices are another matter–consider, for example, that many in Texas are worried that low power prices are discouraging investment in new generation at a time that ERCOT studies suggest new investment will soon be needed. I’ll come back to this question in a later post.

Old data? My primary resources are the 2012 Wind Technologies Market Report (WTMR) produced by the Lawrence Berkeley National Lab, published in August of 2013, and the 2011 Cost of Wind Energy Review (CWER) produced by the National Renewable Energy Lab, published in March 2013.These two document series funded by the Department of Energy are the most recent publications in the longest, most detailed and complete assessments of wind power costs available targeting the U.S. wind industry. I cite to earlier reports in the WTMR and CWER series on a number of occasions when they present relevant discussions of methods and data sources that are not reproduced in the most recent report. A scan through my bibliography shows I cited one document as old as 2004, but the bulk of my citations link to documents published in 2011, 2012, and 2013.

Government estimates instead of market data? Goggin claims, “It is strange that an organization that claims to support free-market price signals would use government estimates instead of price data from signed contracts.” Not at all. The Berkeley Lab and NREL reports are the most frequently cited and likely most authoritative resources available on the topic of wind power costs. The primary point of the my report was to evaluate and provide broader context for understanding the frequently-cited wind cost estimates presented in the Berkeley Lab and NREL reports. For that reason, the report focuses on these “government estimates instead of price data.”

There is more. Cost and price are far from equivalent concepts. Goggin seems to miss this point, but the Berkeley Lab understands. At page 49 of the 2012 WTMR, the report authors said, “because the PPA prices in the Berkeley Lab sample are reduced by the receipt of state and federal incentives (e.g., the levelized PPA prices reported here would be at least $20/MWh higher without the PTC, ITC, or Treasury Grant), and are also influenced by various local policies and market characteristics, they do not directly represent wind energy generation costs.” (Emphasis in the original.)

As even a basic understanding of economics reveals, a subsidy can reduce a price even as it increases the cost of a good or service.

Goggin claims that, because “the average purchase price for wind energy was $40 per MWh in 2011 and 2012,” we can conclude that there are large reductions in cost. Goggin’s $40 per MWh report likely comes from the most recent WTMR, but here is the full sentence with a bit more information:

After topping out at nearly $70/MWh for PPAs executed in 2009, the average levelized price of wind PPAs signed in 2011/2012—many of which were for projects built in 2012—fell to around $40/MWh nationwide, which rivals previous lows set back in the 2000–2005 period.

So prices for contracts in 2011/2012 have returned to levels of the 2000-2005 period? And this is, supposedly, evidence of vast reductions in the cost of wind power, that we are now–after shoveling billions of dollars into the wind power industry post 2005–only now getting wind power contract prices back to the level that they used to be? Goggin’s got more explaining to do if he wants to make an argument using prices to represent costs.

A much more likely explanation is that wind power contract prices depend, in part, on alternative sources of electric power. As natural gas prices rose up through 2008, utilities were willing to pay higher prices for wind power. As natural gas prices fell beginning in late 2008, wind power contract prices fell with them. I’ll hazard the guess that these contract prices have more to do with natural gas prices then reductions in wind power costs.

Up next: Are government subsidies for wind power large or unusual compared to government support for fossil fuels, nuclear power, and other resources?