Electricity Market Structure in Texas: Lessons for the Transition to Renewables

Texas’s electricity market design has been a point of contention since long before the catastrophic events of this past February. The Electricity Reliability Council of Texas (ERCOT) operates on an “energy-only” wholesale market design, meaning that they rely on the price of electricity alone to encourage investment in new generation.

In contrast to the common alternative—having a separate market for capacity—the design feels like a free market leap of faith. For years, electricity market observers have expressed concern as to whether the energy-only design would suffice to ensure the lights stay on in the face of steadily growing power demand.

A crucial part of the design is that wholesale electricity prices in Texas are allowed to be very high during periods when the system is strained. Importantly, this means that market prices are highly sensitive to the amount of generation capacity that is added to the system.

Consider that for simple-cycle natural gas plants, approximately 90 percent of ERCOT real-time market value in 2019 came from only one percent of the hours in that year.¹ Adding even slightly more capacity would have lowered prices during those critical hours, reducing revenue significantly for all generators on the system.

Indeed, investors have lamented that lower wholesale electricity prices caused by, among other things, the addition of wind capacity has meant greater difficulty for power generators to recover costs of new investments, even while the system operator has increased wholesale price caps. Conversely, removing a power plant from the grid has the potential to greatly increase prices during those critical hours, and indeed recent research has shown that large firms may retire capacity early to elevate prices to their advantage.

While wholesale electricity markets are fairly unconcentrated compared to other industries (there were 76 firms operating in ERCOT in 2019), the price sensitivity described above nevertheless carries important implications when it comes to firm incentives to invest in or retire plants.

Take for example Texas’s largest electricity generation firm, Luminant, which comprised approximately 19 percent of the market in 2019. Despite being the largest firm in the market, Luminant has only built only one power plant in the past 20 years (1,600 MW) but has retired 12 plants (totaling about 8,700 MW). This is consistent with the notion that large firms have an incentive to retire plants early to help elevate market prices, as well as a disincentive to build new plants.

The price effects noted above are critical for understanding how firms will respond to policies designed to decarbonize electricity markets. In most cases, policy instruments such as renewable portfolio standards, wind production tax credits, and a carbon tax boil down to different types of price signals. Depending on the policy, an economic assessment may over- or understate the costs of encouraging a transition to renewables (such as a buildout of wind plants) if it does not take market concentration into account. To date most such assessments have not.

While Texas may not be regarded as a champion of climate change policy, the state nevertheless leads the nation in wind generation, with more than 30,000 MW of wind capacity comprising about 20 percent of its generation mix, thanks in no small part to federal wind production subsidies. This experience in scaling up renewables—in the presence of some degree market concentration—offers valuable insights for policy makers.

This post highlights research presented at the Northeast Workshop on Energy Policy and Environmental Economics, hosted this year at the University of Pennsylvania.

Christopher Holt

Doctoral Student, University of Maryland

Christopher Holt is a Ph.D. candidate at the University of Maryland in the Department of Agricultural and Resource Economics. His research applies methods from the field of empirical industrial organization to understand the long-run dynamics of electricity markets.

1. I arrive at this estimate using real-time market prices from ERCOT and generation data from the EPA Continuous Emissions Monitoring System database. I compute real-time market value as the product of settlement point prices and generation. [↩]