The Texas grid operator’s market design is about to experience a true test.
Wholesale electricity markets are in the news, as oversupplied markets drive prices down and force early coal and nuclear retirements. Companies like FirstEnergy have petitioned the federal government for regulatory changes and new market rules to drive up prices and profit margins — but the picture is different in Texas.
The Electric Reliability Council of Texas’ “energy-only” market (EOM) model exposes the value of flexible resources without capacity markets, testing market design in a high-renewables future.
Texas’ market model is working: Market forces are accelerating the transition from dirty, expensive plants to cleaner, cheaper resources including renewables, demand response and batteries. Avoiding capacity markets has saved ERCOT customers billions and kept the system reliable.
But coal retirements and increased load forecasts will put ERCOT’s EOM model to the test. ERCOT’s reserve margin is expected to be significantly below its target this summer, prompting electricity service disruption fears. Market observers are watching closely, as ERCOT does not use capacity markets, the most common alternative for ensuring reliability in markets. These capacity subsidies slow the transition away from uneconomic coal and nuclear while suppressing price signals for flexible units that complement cheaper, cleaner energy resources.
To an unschooled observer, the EOM structure’s test will be whether ERCOT can avoid shortfalls (i.e., a loss-of-load event). But no level of investment or reserve margin can entirely eliminate all risk or protect the grid.
The true test of ERCOT’s market design is whether higher prices spur investment to drive the system back from acceptable risk to a more desirable level of risk. Fortunately, ERCOT looks capable of passing this test, and it should continue avoiding expensive capacity markets.
Will a disruption happen? Putting ERCOT's planning reserve margin in context
A December 2017 planning report prompted concerns that ERCOT’s EOM might not ensure adequate reliability, pegging its summer 2018 expected planning reserve margin (PRM) at 9.3 percent. ERCOT’s PRM has since increased to 11 percent, meaning expected generation fleet capacity exceeds expected summer peak load, minus emergency load management tools (e.g. demand response) by 11 percent.
This is below ERCOT’s 13.75 percent minimum target reserve margin, which reflects ERCOT’s desired risk threshold in line with a resource adequacy standard of “one loss-of-load event in 10 years," where a loss-of-load event (LOLE) is defined as a system deficit triggering rotating outages. However, this summer’s dip below the target PRM doesn’t mean Texas is taking unacceptable systemwide service disruption risks.
Because plenty of uncertainty exists about exactly what level of reserve margin corresponds to a given system risk level, the target PRM is not a magic number, shown by a 2014 Brattle and Astrapé study. The Public Utility Commission of Texas asked them to estimate ERCOT’s economically optimal PRM to inform their ongoing review of market design for resource adequacy, to determine whether ERCOT’s EOM design could deliver desired reliability. Brattle’s top-line results showed widely varying values for possible target reserve margins.
The report includes a wide range of results (12.6 percent to 16.1 percent) for a reliability standard of one event in 10 years (0.1 LOLE), ERCOT’s level of desired reliability risk, in sensitivity cases. This reflects how sensitive an estimate of the desirable PRM is to model assumptions, especially assumptions about the frequency of extreme events. The PRM cannot be a precise measure of reliability risk beyond an accuracy of a couple percentage points.
The PRM resulting from market forces under current rules is called the market equilibrium reserve margin. According to Brattle’s report, ERCOT’s MERM is around 11.5 percent (9.3 percent to 12.9 percent in sensitivities), well short of its 13.75 percent target and resulting in one event in three years (0.33 LOLE) in the models. At this summer’s 11 percent PRM, the study estimates 0.44 LOLE.
The probabilities from this study are quite sensitive to small changes in PRMs and thus can’t be counted on to tell us exactly what ERCOT’s reliability level is for this summer.
Is the risk of system reliability as bad as it seems?
If ERCOT breaches undesirable levels of reliability this summer, how close to the sun will Texas’ grid fly? In other words, is an 11 percent PRM equal to an acceptable level of system risk if new investment will push it back up in coming years?
One fact should help policymakers conclude that Texas is still facing acceptable system risk this summer: Compared to metrics from other jurisdictions, 11 percent seems like an adequate PRM. For example, the one in 10 years resource adequacy standard is a historical construct adopted by the electric power industry that grid operators can interpret differently: “one event in 10 years” could be one day or 24 hours in 10 years (i.e., 2.4 loss-of-load-hours per year). According to Brattle, ERCOT only needs a 9.1 percent PRM to achieve this loss-of-load-hours standard.
Furthermore, reliability from these metrics is more stringent than what customers experience due to distribution-related outages. Suppose this summer ERCOT has an unusually high peak load and reserves dip too low. After a progressive series of steps to add generation from other grids and enlisting large customers who voluntarily are paid to be curtailed during emergencies, ERCOT and the Public Utility Commission of Texas will ask the public to conserve electricity. Once all avenues are played out, ERCOT can institute rotating outages to preserve the entire grid’s integrity — no systemwide blackout would occur.
Rotating outages have only happened three times in ERCOT history, yet even then customers experienced relatively little disruption compared to typical distribution grid problems.
Brattle’s 2014 report explains that even at the lower 2.4 loss-of-load-hours reliability standard, the possibility of rotating outages means customers can expect in a given year to be without power for “only 3 minutes per customer; this compares to an average of a few hundred minutes per customer per year from distribution outages.” The slight possibility of more system-deficit issues is a blip compared to much more common distribution outages.
Finally, the risk of a reliability event this summer is potentially smaller than Brattle’s 50 percent probability because of strong economic incentives in ERCOT’s market design. EOM rewards economic self-interest with prices that spike at times of maximum system stress, and when reserves run short. Price-responsive customers are likely to reduce their load to take advantage of money-saving opportunities.
Combustion turbines and old gas steam plants modeled as having a 19 to 20 percent chance of outage are already gearing up to run during peak demand. The PRM itself has crept up from 9.3 to 11 percent over six months partly through market response to forecasted higher prices.
The real debate: How can energy-only markets adequately mitigate reliability risk?
So, even if a single loss-of-load event in ERCOT happens this summer, it won’t give particularly precise information on whether system risk was at one in three-year or one in 10-year level. While this summer’s planning reserve margin can indicate system reliability risk, understanding the exact connection requires detailed modeling and depends on key assumptions. Because LOLEs happen in addition to more frequent distribution outages, customers won’t likely detect service reliability changes compared to prior years with higher PRMs.
Instead of focusing on PRM, we should examine other metrics to evaluate ERCOT’s near-term health, specifically how frequently the grid calls on all its available resources or faces higher demand than expected — important data for evaluating system reliability risk. Regulators should consider actual resource performance during periods of stress to see if market participants are responding to the immediate performance incentives inherent in an EOM design. Most importantly, regulators should monitor economic signals for increased market participation that the low PRM is sending through forward and real-time markets.
By choosing an EOM, Texas regulators accept that prices will be too low some years to stimulate significant investment, but that this market will also foster investment as prices spike when resources become short. The big questions become: as the PRM varies over various business cycles, where does it average out? And does this average correspond to an acceptable level of reliability?
The business-cycle average is what we earlier referred to as the MERM. This equilibrium matters to policymakers because if it is lower than their benchmark PRM for adequate reliability, than the EOM design is a problem. Policymakers must then further tweak the EOM to increase generator revenues during times of stress, like changes to the operating reserve demand curve or, as a last resort, imposing drastic measures like a capacity market.
According to Brattle’s 2014 report, ERCOT needs a capacity market because its equilibrium of 11.5 percent PRM, remarkably close to this summer’s PRM, falls short of its 13.75 percent target and the 14.1 percent PRM that achieves a one-in-10 LOLE. Brattle estimated long-term capacity market incremental costs to customers at $400 million per year, a 1 percent bill premium. Even so, the PUCT continued trusting the market and Texas consumers have benefited greatly.
Texas should let the market work as designed
Despite the PRM dropping below benchmark, Texas should stay the course. Apart from capacity market shortcomings and inefficiencies, Brattle’s modeling may underestimate market response to a low PRM, meaning the EOM should financially support an adequate level of risk.
Forward prices (see ICE) are very high for this summer ($120 per megawatt-hour and $220 megawatt-hour average 7 a.m.-10 p.m. for July and August as of May 10). Based on such prices, combined-cycle gas plants could easily make revenues net of short-term expenses more than 200-250 percent what’s necessary to recover annualized long-term capital expenses — significant incentive to invest in new gas resources.
Furthermore, the marginal new build may not be a combined-cycle gas plants or gas peaker plant, with associated build-time lag. Resources like wind, batteries, solar, reciprocating engines and demand response can — and will — come online much more quickly in this pricing environment.
Instead of revisiting fixes like capacity markets, Texas policymakers should let markets show their stuff while focusing on continual improvement to energy-market efficiency that maintains acceptable risk. For example, improving the availability of price-responsive demand (lowers costs and the need for reserves), or promoting policies to improve the finances of new clean resources by improving the creditworthiness of load counterparties (like retailers) that use them to hedge exposure to soaring prices like those expected this summer.
By doubling down on its faith in markets, Texas can continue to demonstrate a market-driven transition to a cleaner, cheaper and more reliable grid.