Energy Economics, Regime Changes, and Sustainability
Saturday, Jan. 6, 2018 12:30 PM - 2:15 PM
- Chair: Alberto J. Lamadrid, Lehigh University
What’s killing nuclear power in U.S. electricity markets? Drivers of wholesale price declines at nuclear generators in the PJM Interconnection
AbstractElectricity market prices across organized wholesale electricity markets in the United States have declined significantly in recent years, prompting several nuclear power stations to consider early retirement before the end of their licensed operation or useful lifespans. This paper explores three possible explanations for observed declines in day-ahead electricity prices received by 19 nuclear generators in the PJM electricity market region: (1) the impact of declining natural gas prices; (2) the growth of wind generation in the American Midwest; and (3) stagnant or declining demand for electricity. I employ time series linear regression with time fixed effects to empirically estimate the effect of each explanatory variable on the average day-ahead locational marginal price (LMP) earned by 19 nuclear generating stations (with 33 individual reactors) located in PJM (encompassing roughly one-third of the U.S. nuclear fleet) as well as weighted average PJM day-ahead market prices. The paper uses daily average observations from January 1, 2008 to December 31, 2016 (n = 3,288). I employ a variety of alternative specifications to further explore geographic heterogeneity in causal effects on different generators across the PJM region and interrogate the impact of using price time series from different natural gas trading hubs. I find that natural gas price declines are the dominant driver of reduced electricity prices at the 19 nuclear power stations over this period. The growth of wind energy has an order of magnitude smaller cumulative effect and is only statistically significant for nuclear generators located in the western portion of the PJM region (in proximity to vast majority of installed wind capacity in the region). Finally, declining demand also has a relatively small but statistically significant effect on prices across all generators.
Gasoline Savings From Clean Vehicle Adoption
AbstractWithout the option to purchase plug-in electric and/or hybrid vehicles, conventional counterfactuals used in the literature may underestimate the fuel savings from clean vehicle adoption, thus overestimating the costs of securing associated environmental benefits. Using a nationally representative sample of new car purchases in the U.S., we propose a vehicle choice model-based counterfactual approach that allows us to predict what consumers would purchase if these clean vehicles were unavailable. The choice model results suggest that the gasoline consumption under a no clean vehicle scenario increases by 1.71 percent, compared to a 1.14 percent increase based on a conventional counterfactual. Many pivotal buyers would instead purchase premium brands and larger vehicles, leading to an increase in the share of light trucks, which are subject to less stringent, but more difficult to meet, standards. Lastly, we estimate the cost of demand-side policies in the form of financial incentives to encourage plug-in electric vehicle adoption. Assuming a vehicle lifetime of 10 years, the conventional counterfactual overestimates the cost of gasoline savings at $8.75 per gallon compared to $6.90 per gallon estimated from the choice model-based counterfactual.
Who Pays In Deregulated Electricity Markets?
AbstractLike many other “coal states,” Ohio has undergone tremendous regulatory regime change in the past decade. It has introduced competition into both its wholesale and retail electricity markets, making it an exemplary case for evaluating the economic effects of regulatory change and resource transition. Empirical support for the purported benefits of retail electric deregulation is mixed at best. Prior studies that refer to states as simply “retail deregulated” overlook the fact that efforts in many states to introduce retail competition have been muddied by various degrees of regulatory intervention. Those studies are often based upon Energy Information Administr ation (EIA) 826 data that does not account for large costs that end-customers incur from regulatory intervention—which amount to more than 50 percent of the total bill in states like Ohio. Using robust time series bill survey data from the Public Utilities Commission of Ohio (PUCO), this paper provides a quasi-experimental analysis of the price impacts of retail electric restructuring in Ohio on all customer classes—residential, commercial, and industrial. It provides measures of the effect of regulatory change on inter-class subsidization (i.e., subsidies from residential customers to commercial and industrial customers). We also provide welfare impact estimates for each utility service territory.
We employ a data source that has not yet been used in academic literature (with the exception of Dormady, Jiang and Hoyt, 2017). While the majority of ‘deregulation’ research has used EIA data, that data is flawed in that it only captures the costs that utilities report from transactions at a wholesale market level, and does not reflect costs associated with riders and surcharges that customers incur at a retail level from utilities’ efforts to subsidize the assets of utility-owned, non-regulated subsidiary businesses. Riders and surcharges amount to more than half of customer total bills.
Federal Reserve Bank of Dallas
London Economics International
Fred B. Olayele,
University of Pittsburgh
- L9 - Industry Studies: Transportation and Utilities
- Q4 - Energy