Power Plants Too Big to Fail?

The San Onofre Nuclear Generating Station (SONGS) was closed abruptly in February 2012. During the previous decade, SONGS had produced about 8% of the electricity generated in California, so its closure had a pronounced impact on California’s wholesale electricity market, requiring large and immediate increases in generation from other sources.

In a new EI@Haas Working Paper titled, “The Value of Transmission in Electricity Markets: Evidence from a Nuclear Power Plant Closure”, we use publicly available data to examine the impact of the closure on economic and environmental outcomes. Because of the plant’s size and prominence, the closure provides a valuable natural experiment for learning about firm behavior in electricity markets.

We find that the SONGS closure increased the cost of electricity generation by $370 million during the first twelve months. This is a large change, equivalent to a 15% increase in total generation costs. The SONGS closure also had important implications for the environment, increasing carbon dioxide emissions by 9.2 million tons over the same period. Valued at $35 per ton (IWG 2013), this is $330 million worth of emissions, the equivalent of putting more than 2 million additional cars on the road.

The closure was particularly challenging because of SONGS’ location in a load pocket between Los Angeles and San Diego. Transmission constraints and other physical limitations of the grid mean that a substantial portion of Southern California’s generation must be met locally. When SONGS closed, these constraints began to bind, essentially segmenting the California market. The figure below shows the price difference at 3 p.m. on weekdays between Southern and Northern California. After the closure there were many more days with positive differentials, including a small number of days in which prices in the South exceeded prices in the North by more than $40 per megawatt hour.

These binding transmission constraints meant that it was not always possible to meet the lost output from SONGS using the lowest cost available generating resources. Southern plants were used too much, and Northern plants weren’t used enough. Of the $370 million in increased generation costs, we attribute about $40 million to transmission constraints and other physical limitations of the grid. This number is less precisely estimated than the overall impact, but is particularly interesting in that it provides a measure of the value of transmission.

The paper provides all the gory details about how we made these calculations. It turns out to be more difficult than a simple before-and-after comparison because during this period the California market was also experiencing a whole set of simultaneous changes to hydroelectric resources, renewables, demand, and fuel prices. What is helpful, however, is that transmission constraints were rarely binding prior to the closure. This means that observed behavior during the pre-period provides a good sense of how firms would have behaved during the post-period had there not been transmission constraints.

Our findings provide empirical support for long-held views about the importance of transmission constraints in electricity markets (Bushnell 1999; Borenstein, Bushnell and Stoft 2000; Joskow and Tirole 2000), and contribute to a growing broader literature on the economic impacts of infrastructure investments (Jensen 2007, Banerjee, Duflo and Qian 2012, Borenstein and Kellogg 2014).

The episode also illustrates the challenges of designing deregulated electricity markets. A new book chapter by Frank Wolak (here) argues that while competition may improve efficiency, it also introduces cost in the form of greater complexity and need for monitoring. Transmission constraints add an additional layer to this complexity, by implicitly shrinking the size of the market. Constraints increase the scope for non-competitive behavior, but only for certain plants during certain high-demand periods, so understanding and mitigating market power in these contexts is difficult and requires a sophisticated system operator.

energy at haas