A recent article “Heterogeneous Solar Capacity Benefits, Appropriability, and the Costs of Suboptimal Siting” in the Journal of the Association of Environmental and Resource Economists finds that distributed solar (e.g., rooftop solar) is not being installed a manner that “optimally” mitigates air pollution damages from electricity generation across the U.S. Unfortunately the paper is built on two premises that do not reflect the reality of available options and appropriate pricing signals.
First, the authors appear to be relying on the premise that sufficient solar, grid-scale or distributed, can be installed cost-effectively across the U.S. While the paper includes geographic variations in generation per installed kilowatt of capacity, it says nothing about the similarly widely varying costs per kilowatt-hour. They do not acknowledge that panels in the Pacific Northwest will cost twice that of those in the Desert Southwest. This importance of this disparity is compounded by the underestimate of the social cost of carbon and the possible conflation of sulfur dioxide and particulate matter damages. The currently accepted social cost of GHG emissions developed by the U.S. Environmental Protection Agency (US EPA) is ranges from $50 to $150 per tonne in 2030 (and recent studies have estimated that this is too low), compared to the outdated $41 per tonne in the article. Most of the SO2 damages arise from creating PM so there is likely double counting for these criteria pollutants. (The study also ignore the strong correlation between GHG and SO2 emissions as coal is the biggest source of both.) The study also fails to account for the enormous transmission costs that would be incurred moving solar output from the Desert Southwest to the Northeast to mitigate the purported damages.
Second, the authors try to claim that rooftop solar has not relieved transmission congestion by looking at grid congestion prices. The problem is that this method is like looking at an empty barn and saying a horse never lived there. Congestion pricing is based on the current transmission capacity situation. It says nothing about the history of transmission congestion or the ability and efforts to look forward to mitigate congestion. The study found that congestion prices were often negative or small in areas with substantial rooftop solar capacity. That doesn’t show that the solar capacity has little value–instead it shows that it actually relieved the congestion effectively–a completely opposite conclusion.
In contrast, the California Independent System Operator (CAISO) calculated in 2017 (contemporaneously with the article’s baseline) that at least $2.6 billion in transmission projects had been deferred. And given the utilities’ poor records on load forecasting, these savings have likely grown substantially. CAISO had anticipated and already relieved the congestion that the authors’ purported metric was searching for.
This disparity in economic results highlights the nature of investing in long-lived infrastructure that requires multiple years to build–one cannot wait for a shortfall to emerge to respond because that’s too late. Instead, one must anticipate those events and act even when its uncertain. This study is yet another example of how relying on the premise that short-run electricity market prices are reflective of long-run marginal costs is mistaken and should be set aside for policy analysis.
Economics Outside the Cube 