Looking for renewable policy certainty in all the wrong places

From EnergyWire comes the headline, “In Missouri, industry wants off the ‘solar coaster’.” (link here via Midwest Energy News).

A utility rebate program authorized by voters in 2008 is making Missouri into a solar leader in the Midwest. But $175 million set aside to subsidize solar installations is [nearly] fully subscribed … and the same small businesses that scrambled to add workers last year to help meet surging demand are facing layoffs….

Heidi Schoen, executive director of the Missouri Solar Energy Industries Association, said the industry, which has generated thousands of jobs and millions of dollars in new taxes for the state, is just looking for certainty.

“We want off the solar coaster,” she said. “We don’t want to be in this boom-and-bust situation.”

It is a patently false claim.

If they wanted off of the boom-and-bust policy ‘solar coaster,’ they’d get off. They could go do unsubsidized solar installations for example, or if (when?) that proves unprofitable get work doing something else. By their actions they signal that they prefer the booms-and-busts that come with reliance on politicians for favors.

Better red than dead, but not red yet (on solar power)

In her New York Times Economix column Nancy Folbre recently said (“The Red Faces of the Solar Skeptics,” March 10, 2014):

If the faces of renewable energy critics are not red yet, they soon will be. For years, these critics — of solar photovoltaics in particular — have called renewable energy a boutique fantasy. A recent Wall Street Journal blog post continues the trend, asserting that solar subsidies take money from the poor to benefit the rich.

But solar-generated electricity is turning into a powerful environmental and economic success story. It’s also threatening the balance sheets of electric utility companies that continue to rely heavily on fossil fuels and nuclear energy.

I don’t count myself a renewable energy critic, but I do find myself as a critic of most renewable energy policies and so feel a bit like Folbre is addressing her points to me. In response I’ll say my face isn’t red yet, and I’m not expecting it to turn red anytime soon.

Folbre is a distinguished economist at the Univ. of Massachusetts, but she isn’t a specialist in environmental or energy economics, and I think her thinking here is a little muddled. (In this muddling through she has similarly distinguished company–consider this response to a Nobel prize winner.)

So a sample of my complaints: She trumpets the fast declining price of solar panels by picking a factoid out of a story in ComputerWorld: “declined an estimated 60 percent since the beginning of 2011!” ComputerWorld? Maybe the work of the U.S. Department of Energy or other more traditional information sources wasn’t sensational enough (claiming as it does, merely that “U.S. solar industry is more than 60 percent of the way to achieving cost-competitive utility-scale solar photovoltaic electricity”).

An investment company would have to acknowledge that cherry-picked past results are no guarantee of future performance, but it isn’t even clear that she is firm on the idea of “cost.” Folbre declares that generous subsidies and feed-in tariffs have “allowed solar photovoltaics to achieve vastly lower unit costs.” Really? Well maybe if we subsidize it a little harder, it will become free for everyone!

C’mon professor, get serious! Perhaps it is true that generous subsidies and feed-in tariffs have allowed owners of solar PV systems to experience lower out-of-pocket expenses, but it is a little embarrassing to see a distinguished economist make this mistake about costs. Should we conclude congressional junkets overseas don’t cost anything because the government foots the bill?

Not until the penultimate paragraph does Folbre get back on firm ground, talking about renewable energy policy rather than technology:

Subsidies are not the ideal public policy for promoting clean energy. As a recent analysis by the Carbon Tax Center points out, a carbon tax devised to protect low-income households from bearing a disproportionate share of higher energy prices would yield more efficient overall results, as well as encouraging solar power.

But in our subsidy-encrusted energy economy, some subsidies are better than others. As farmers say, make hay while the sun shines.

Yes, as any economist ought to say, “subsidies are not the ideal public policy for promoting clean energy.” In fact, it’s been said here a time or two.

[HT to Environmental Economics.]

Someone please explain the American Wind Energy Association’s funky electricity price arithmetic

About a month ago the American Wind Energy Association blogged: “Fact Check: New Evidence Rebuts Heartland’s Bogus RPS Claims.” I’m scratching my head a bit trying to understand their so-called facts. The big claim from AWEA:

The eleven states that produce more than seven percent of their electricity from wind energy have seen their electricity prices fall 0.37 percent over the last five years, while all other states have seen their electricity prices rise by 7.79 percent.

The blog post mentions DOE data, and the post links to a report the AWEA assembled titled “Wind Power’s Consumer Benefits” which cites U.S. EIA data on “Average Retail Price of Electricity to Ultimate Customers” (find the data here). The blog doesn’t explain their method and the report is only barely more helpful in that regard.

The AWEA report describes the price suppressing “merit order” effect of subsidized/low marginal cost wind energy, but that is a wholesale price phenomena that doesn’t include various other utility compliance costs, and anyway the AWEA is making claims about end consumer benefits from lower retail prices. The merit order effect only matters to consumers if consumers end up paying lower retail prices.

So I downloaded data from the EIA site and tried to calculate the retail percent change in price for every state over the last five years, then compared the eleven states that AWEA said produce more than seven percent of their electricity from wind energy to the remaining states and DC.

By my simple average, prices in the 11 “wind states” were about 18.8 percent higher in December 2013 than they were in December 2008; prices in the 39 other states and DC were about 5.7 percent higher in December 2013 than they were in December 2008. Now maybe AWEA is doing a weighted average by kwh sold or something different than my straightforward calculation, but they don’t explain it and I can’t reproduce it.

Can you?

The price data from December 2008 and December 2013 for the eleven “wind states” and “Avg-All Others” are:

State Dec-08 Dec-13 Percent change
Iowa          7.10          7.77 9.4%
Kansas          7.01          9.19 31.1%
Minnesota          7.66          9.27 21.0%
North Dakota          6.35          8.03 26.5%
South Dakota          6.93          8.57 23.7%
Oklahoma          6.55          7.14 9.0%
Texas        10.85          8.77 -19.2%
Colorado          8.01          9.48 18.4%
Idaho          5.97          7.91 32.5%
Wyoming          5.68          7.71 35.7%
Oregon          7.24          8.61 18.9%
Avg-All Others        10.60        11.19 5.7%
* Prices are cents/kwh

I can’t help but notice that only one of the 11 wind states (Texas) saw a decline in prices over the time period, and the other 10 wind states actually saw prices increase from December 2008 to December 2009 faster than the overall average of the other states.

So what kind of funky AWEA arithmetic turns (mostly) larger retail price increases in the 11 states into a big consumer benefit?

NOTE: By the way, a sophisticated attempt to address the questions of wind power’s consumer benefits-if any on net-would look at a lot more information than simple average retail rates by states. I was trying to engage the debate on the level presented and even at this simple level of analysis I can’t tell how they got their numbers.

Discrimination in West Virginia price gouging case?

Are West Virginia “outsiders” more likely to be accused of price gouging?

From the March 8, 2014, Charleston Gazette, “Morrisey accused of discrimination in price gouging response“:

CHARLESTON, W.Va. –A Putnam County storeowner accused of price gouging bottled water during the water crisis says Attorney General Patrick Morrisey discriminated against him because he is Lebanese, questioned him unethically and illegally leaked the charge to the media before informing him of it.

On Feb. 14, Morrisey filed suit in Putnam Circuit Court alleging that Achraf Assi’s convenience stores, Hurricane-based Mid Valley Mart LLC, unfairly raised the price of Tyler Mountain Spring Water from $1.59 a gallon to $3.39 a gallon the day after the Jan. 9 chemical leak that contaminated the region’s drinking water.

Morrisey alleged that Assi, who owns the two stores that allegedly sold water at inflated prices, kept the prices higher for a week following the chemical leak.

In this news report the West Virginia Attorney General refers to alleged price gougers as “bad apples.”

The attorney general’s office reported over 150 calls concerning prices during the water emergency and documented 74 cases of increased prices on water and other goods. As of late February, the AG’s office reported issuing six subpoenas and 15 cease and desist letters. Only one price gouging case has been filed subsequent to the water emergency.

So far as I am aware, this is the first time I’ve seen claimed that price gouging laws have been implemented in a discriminatory fashion.

In 2012 I suggested the possibility that price gouging laws could be applied in discriminatory fashion (here and here). In brief, my claim was (1) the laws typically grant some discretion to the state, and any discretion exercised was unlikely to favor “outsider” groups; and (2) enforcement is almost always triggered by consumer complaint and so gives any consumer bias a role in anti-price gouging law enforcement. I’ve also speculated that “outsider” merchants may be more likely to raise prices in response to emergencies, but know of no research on that possibility.

No net metering without grid connection, no net metering controversy where wires and energy products are unbundled

Around the country lobbyists for utilities and solar power companies are fighting over public policy, mostly for and against reform of net metering policies.* Today, The Alliance for Solar Choice (TASC) trumpeted in a press release recent victories in the states of Utah and Washington over net metering reforms urged by utilities. TASC highlighted the involvement of conservative policy group the American Legislative Exchange Council (ALEC), which joined the battle over net metering via a January 2014 resolution calling for “policies to require that everyone who uses the grid helps pay to maintain it and to keep it operating reliably at all times.”

In the TASC press release the group makes the odd and laughable claim:

Net metering allows rooftop solar customers to … receive full retail credit for any excess electricity sent back to the grid. Utilities turn around and sell this energy at the full retail rate to the neighbors, even though they paid nothing to generate, transmit or distribute that cleaner power.

I wonder how TASC thinks the net-metered customers’ excess electrical power actually flows to the neighbor’s property?

On the other hand, I take the next sentence in the TASC press release as obviously true: “Utilities attacking net metering want to eliminate the policy to stifle energy choice and protect their monopolies.” Evidence for the point is contained in the Washington state bill which, in addition to reforming net metering would have banned third party financing of rooftop solar if the utility itself offered a leasing program.

But one can oppose net metering and still favor “energy choice.” In fact, net metering is in the end incompatible with energy choice since net metering requires a grid connection and a cross-subsidy from grid-connected, non-net metered customers to survive. Giving energy choice to the customers subsidizing their solar-paneled neighbors will, if the burden grows large enough, push unsubsidized customers off the grid.

Currently, the burden is rather small most places. The utility industry is worried, though, about the possible rapid spread of net metering as the economics of rooftop solar improve and the consequent rate “death spiral” as fewer and fewer customers remain who actually pay for the costs of local distribution systems. See the report Disruptive Challenges, distributed by EEI in early 2013, and now the Economics of Grid Defection, published by the Rocky Mountain Institute this year.

The fight over net metering and other rooftop solar policies has broken out in a number of states, from Georgia to Massachusetts to Wisconsin to the solar-rich states of California and Arizona. Perhaps most interesting, however, is to note one solar-rich state lacking a battle over net metering: Texas. As Lynne noted here last summer, with generation and retailing already divorced from the monopoly wires business (in most of the state), Texas’s wires utilities are not nearly as threatened by distributed generation resources.

Power retailers in Texas are free (within limits) to offer a variety of contract to customers with distributed generation capability, and at least one offers a net metered-style product. Reliant’s e-Sense Sell-back plans credit customers for the full retail energy rate for the first 500 kwh of power put onto the grid (about $0.17 kwh at peak prices, and any additional power at $0.05 per kwh). Notice that as Reliant is an unregulated retail power provider, not a regulated utility, there is no forced cross-subsidization of distributed energy resources in the offering.

No subsidy, no undermining of grid finances, supports energy choice without promoting energy poverty. What is not to like?

 

 

*Net metering policies allow consumers capable of self-generation to be credited for any generation put onto the local distribution grid at the full retail price of electricity. Because the full retail price of electricity covers both energy and grid costs, utilities object that net metered customers are overpaid for the power they inject into the distribution grid.

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.

One year after Superstorm Sandy: Charities, price gougers and the state

Popular Mechanics magazine headlined an article with the question, “One year after Superstorm Sandy, has anything changed?

Well, sure: over the last year the state governments in New York and New Jersey have put a lot of time and money into punishing a few businesses that provided shelter and gasoline to people whose lives were disrupted by the storm. Why, you ask? Because the prices offered by these businesses after the storm hit were somewhat higher than the prices offered by the businesses before the storm hit.

One example, a Holiday Inn Express in Brooklyn recently agreed to pay a total of $40,000 to settle a complaint, part of it to customers and part to the state, because the state concluded the $400+/night rate charged to the customers was too much higher than the $170/night rate charged the week earlier.

As is perhaps obvious, government prosecution of post-emergency price-raising retailers will produce real world consequences. The question for economists is whether on balance the costs of the policies are worth the benefit secured. So far as I know there is no study that tries to answer this question in a comprehensive manner. (Best effort so far: here.)

In related news, the New York Attorney General’s office has reached an agreement with four charities that had collected money to help Sandy victims but not yet spent all of the funds. Under the agreement the four groups committed to a time table for spending most of the remaining funds.

Charities and for-profit enterprises both have provided many useful goods and services to people whose lives were disrupted by Sandy. If the soft price cap imposed by price gouging restrictions reduces for-profit supply responses during emergencies, then the restrictions add to the hardships that charities seek to address (and perhaps also to public demands that government do something, even something foolish).

At Bleeding Heart Libertarians, Matt Zwolinski continues to explore price gouging issues in a couple of recent posts. In “Price gouging and the poor” he takes on the common claim that state laws against price gouging are particularly valuable for protecting poor persons. In “World Cup ‘price gouging’?” he examines the Brazilian government’s declaration it will monitor hotel room prices for the upcoming 2014 World Cup competition and act to prevent abuses. Given that most people willing and able to travel internationally to attend World Cup matches in Brazil next year are far from poor, the two posts make a nice pair. (Related is my February 2012 post “Super Bowl price gouging complaints.”)

Saudi Arabia and OPEC oil output

A careful comparison of Saudi Arabia’s oil production behavior with rest-of-OPEC production provides a way to see the consistency in Saudi behavior where many analysts have missed it, according to the authors of a report forthcoming in the journal Energy Policy. Sometimes Saudi and rest-of-OPEC production movements are positively correlated and other times negatively correlated–a relation that hides the consistency in Saudi policy according to the authors. But if stability of the world oil market post-1973 is identified as the Saudi goal, it can be seen that Saudi acts jointly with rest-of-OPEC to reduce output at times of declining world demand but works to counteract rest-of-OPEC declines by boosting output during supply interruptions elsewhere.

Here is a bit more from the introduction to the article:

OPEC quadrupled crude oil prices nearly 40 years ago, and since then we have witnessed a large literature about how OPEC and its key producers have acted within the world oil market. A substantial part of this literature stems from the analysis by Griffin (1985).1 Yet there has been surprisingly little agreement about some of the most important questions, such as the role of Saudi Arabia and whether it coordinates its production decisions with its partners in OPEC. Smith (2005, p. 75) does not find clearly discernible consistency in the actions of Saudi Arabia, while Kaufmann et al. (2008, p. 348) find no clear relationship between Saudi production and that from the Rest of OPEC.

This article re-examines these questions, with a special focus on Saudi Arabia’s decisions about its levels of oil production and exports.2 Although others have used a single model for Saudi Arabia over time, we believe that Saudi behavior has varied, depending upon the circumstances.3 In many years Saudi Arabia has acted together with the Rest of OPEC, restricting its exports together with its OPEC partners as demand declined, and expanding its exports when demand increased. The most notable examples of proportional restriction in exports during recessions are 1974–1975, 1998, 2002, and in 2008–2009. At other times, however, the Saudis have acted independently from the Rest of OPEC, most notably at those times of supply interruption elsewhere in OPEC: 1978 in Iran, 1980–1981 in Iraq and Iran, 1990 in Kuwait and Iraq, 2003 in Iraq, 2011 in Libya. On these occasions, rather than matching the export cutbacks elsewhere in OPEC, the Saudis increased their exports to offset the interruptions.4

This variation in Saudi export behavior over time is evident in the correlation between the changes in Saudi oil exports and changes in exports from the Rest of OPEC. In most “normal” periods (excluding interruptions and recoveries), the correlation is relatively high, at about 0.7. But during interruptions the correlation becomes negative. Although the average correlation since 1973 is 0.19, this masks the wide variation over time: strongly positive during “normal” periods but negative during and after supply interruptions.

We analyze these different periods separately, distinguishing between normal periods and interruptions, and between increases and decreases in Saudi exports. Within this complexity, we find consistent behavior by Saudi Arabia.

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The authors of the article are Khalid Alkhathlan, Dermot Gately, and Muhammad Javid.