Tag Archives: ERCOT

Why utility prices cannot be set using short-run marginal costs

One commentator on the Energy Institute at Haas’ blog entitled “Everyone Should Pay a ‘Solar Tax’” points out that one version of economic theory holds that short run marginal cost is the appropriate metric for composing efficient prices. And he points out that short-run (SRMC) and long-run marginal costs (LRMC) should converge in equilibrium. So he implicitly says that long run marginal costs are the appropriate metric if as a stable long-run measure is based, as he states, on forecasts.

Even so, he misses an important aspect–using the SRMC for pricing relies on important conditions such as (1) relatively free entry and exit, (2) producers bear full risk for their investments, and (3) no requirements exist for minimum supply (i.e., no reserve margins). He points out that utilities overbuild their transmission and distribution (and I’ll point out their generation) systems. I would assert that is because of the market failures related to the fact that the conditions I listed above are missing–entry is restricted or prohibited, customers bear almost all of the risk, and reserve margins largely eliminates any potential for scarcity rents. In fact, California explicitly chose its reserve margin and resource adequacy procurement standards to eliminate the potential for pricing in the scarcity rents necessary for SRMC and LRMC to converge.

He correctly points out that apparent short run MC are quite low (not quite as close to zero as he asserts though)–a statement that implies that he expects that SRMC in a correctly functioning market would be much higher. In fact, as he states, the SRMC should converge to the LRMC. The fact is that SRMC has not risen to the LRMC on an annual average basis in decades in California (briefly in 2006, 2001 and 2000 (when generators exerted market power) and then back to the early 1980s). So why continue to insist that we should be using the current, incorrect SRMC as the benchmark when we know that it is wrong and we specifically know why its wrong? That we have these market failures to maintain system reliability and address the problems of network and monopolistic externalities is why we have regulation.

The solution is not to try to throw out our current regulatory scheme and then let the market price run free in the current institutional structure with a single dominant player. Avoiding market dominance is the raison d’etre for economic regulation. If that is the goal, the necessary first step is introducing and sustaining enough new entrants to be able to discipline the behavior of the dominant firm. Pricing reform must follow that change, not precede it. Competitive firms will not just spontaneously appear due to pricing reform.

It’s not clear that utilities “must” recover their “fixed” investments costs. Another of the needed fixes to the current regulatory scheme to improve efficiency is having utilities bear the risks of making incorrect investment decisions. Having warned (correctly) the IOUs about overforecasting demand growth for more than a dozen years now, they will not listen such analyses unless they have a financial incentive to do so.

Contrary to claims by this and other commentators, It is not efficient to charge customers a fixed charge beyond the service connection cost (which is about $10/month for residential customers for California IOUs). If the utility charges a fixed cost for the some portion of the rest of the grid, the efficient solution must then allow customers to sell their share of that grid to other customers to achieve Pareto optimal allocations among the customers. We could set up a cumbersome, high transaction cost auction or bulletin board to facilitate these trades, but there is at least another market mechanism that is nearly as efficient with much lower transaction costs–the dealer. (The NYSE uses a dealer market structure with market makers acting as dealers.) In the case of the utility grid, the utility that operates the grid also can act as the dealer. The most likely transaction unit would bein kilowatt-hours. So we’re left back where we started with volumetric rates. The problem with this model is not that it isn’t providing sufficient revenue certainty–that’s not an efficiency criterion. The problem is that the producer isn’t bearing enough of the risk of insufficient revenue recovery.

An alternative solution may be to set the distribution volumetric rate at the LRMC with no assurance of revenue requirement on that portion, and then recover the difference between average cost and LRMC in a fixed charge. This is the classic “lump sum” solution to setting monopoly pricing. The issue has been how to allocate those lump sum payments. However, the true distribution LRMC appears to be higher than average costs now based on how average rates have been rising.

ERCOT has the peak period scarcity price too high

The freeze and resulting rolling outages in Texas in February highlighted the unique structure of the power market there. Customers and businesses were left with huge bills that have little to do with actual generation expenses. This is a consequence of the attempt by Texas to fit into an arcane interpretation of an economic principle where generators should be able to recover their investments from sales in just a few hours of the year. Problem is that basic of accounting for those cashflows does not match the true value of the power in those hours.

The Electric Reliability Council of Texas (ERCOT) runs an unusual wholesale electricity market that supposedly relies solely on hourly energy prices to provide the incentives for incenting new generation investment. However, ERCOT is using the same type of administratively-set subsidies to create enough potential revenue to cover investment costs. Further, a closer examination reveals that this price adder is set too high relative to actual consumer value for peak load power. All of this leads to a conclusion relying solely on short-run hourly prices as a proxy for the market value that accrues to new entrants is a misplaced metric.

The total ERCOT market first relies on side payments to cover commitment costs (which creates barriers to entry but that’s a separate issue) and second, it transfers consumer value through to the Operating Reserve Demand Curve (ORDC) that uses a fixed value of lost load (VOLL) in an arbitrary manner to create “opportunity costs” (more on that definition at a later time) so the market can have sufficient scarcity rents. This second price adder is at the core of ERCOT’s incentive system–energy prices alone are insufficient to support new generation investment. Yet ERCOT has ignored basic economics and set this value too high based on both available alternatives to consumers and basic regional budget constraints.

I started with an estimate of the number of hours where prices need the ORDC to be at full VOLL of $9000/MWH to recover the annual revenue requirements of combustion turbine (CT) investment based on the parameters we collected for the California Energy Commission. It turns out to be about 20 to 30 hours per year. Even if the cost in Texas is 30% less, this is still more 15 hours annually, every single year or on average. (That has not been happening in Texas to date.) Note for other independent system operators (ISO) such as the California ISO (CAISO), the price cap is $1,000 to $2,000/MWH.

I then calculated the cost of a customer instead using a home generator to meet load during those hours assuming a life of 10 to 20 years on the generator. That cost should set a cap on the VOLL to residential customers as the opportunity cost for them. The average unit is about $200/kW and an expensive one is about $500/kW. That cost ranges from $3 to $5 per kWh or $3,000 to $5,000/MWH. (If storage becomes more prevalent, this cost will drop significantly.) And that’s for customers who care about periodic outages–most just ride out a distribution system outage of a few hours with no backup. (Of course if I experienced 20 hours a year of outage, I would get a generator too.) This calculation ignores the added value of using the generator for other distribution system outages created by events like a hurricane hitting every few years, as happens in Texas. That drives down this cost even further, making the $9,000/MWH ORDC adder appear even more distorted.

The second calculation I did was to look at the cost of an extended outage. I used the outages during Hurricane Harvey in 2017 as a useful benchmark event. Based on ERCOT and U.S. Energy Information Reports reports, it looks like 1.67 million customers were without power for 4.5 days. Using the Texas gross state product (GSP) of $1.9 trillion as reported by the St. Louis Federal Reserve Bank, I calculated the economic value lost over 4.5 days, assuming a 100% loss, at $1.5 billion. If we assume that the electricity outage is 100% responsible for that loss, the lost economic value per MWH is just under $5,000/MWH. This represents the budget constraint on willingness to pay to avoid an outage. In other words, the Texas economy can’t afford to pay $9,000/MWH.

The recent set of rolling blackouts in Texas provides another opportunity to update this budget constraint calculation in a different circumstance. This can be done by determining the reduction in electricity sales and the decrease in state gross product in the period.

Using two independent methods, I come up with an upper bound of $5,000/MWH, and likely much less. One commentator pointed out that ERCOT would not be able achieve a sufficient planning reserve level at this price, but that statement is based on the premises that short-run hourly prices reflect full market values and will deliver the “optimal” resource mix. Neither is true.

This type of hourly pricing overemphasizes peak load reliability value and undervalues other attributes such as sustainability and resilience. These prices do not reflect the full incremental cost of adding new resources that deliver additional benefits during non-peak periods such as green energy, nor the true opportunity cost that is exercised when a generator is interconnected rather than during later operations. Texas has overbuilt its fossil-fueled generation thanks to this paradigm. It needs an external market based on long-run incremental costs to achieve the necessary environmental goals.

Chasing gold at the end of the rainbow: how reliance on hourly markets doesn’t spur generation investment

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Commentators have touted the Texas ERCOT market as the epitome of how a fully functioning hourly electricity market can deliver the economic signals needed to spur investment in new capacity. They further assert that this type of market can be technology neutral in what type of investment is made. The Federal Energy Regulatory Commission (FERC) largely adopted this position more than two decades ago when it initiated restructuring that led to the creation of these hourly markets, including the California Independent System Operator (CAISO). And FERC continues to take that stance, although it has allowed for short term capacity markets to backfill for reliability needs.

But now we hear that the Texas market is falling short in incenting new capacity investment. ERCOT which manages the Texas grid projects near term risks and a growing shortfall at least to 2024. At issue is the fact that waiting around for the gambler’s chance at price spike revenues doesn’t make a strong case for financing capital intensive generation, particularly if one’s own investment is likely to make those price spikes disappear. It’s like chasing the gold at the end of the rainbow!

This is another sign that hourly markets are not reliable indicators of market value, contrary to the view of proponents of those markets. The combination of the lumpiness of generation investment and the duration of that generation capital, how that new generation undermines the apparent value in the market, and the lack of political tolerance for failures in reliability or meeting environmental targets require that a much more holistic view of market value for these investments. The value of hedging risk, providing cost stability, improving reliability and resilience and reducing overall portfolio costs all need to be incorporated into a full valuation process.