Do Day-Ahead Electricity Prices Reflect Economic Fundamentals? Evidence from the California ISO.

AuthorForbes, Kevin F.
  1. INTRODUCTION

    To neoclassical economists, market prices are the primary signals ensuring efficient resource allocation. While many might concede that markets "work" in the abstract, events like the California power crisis of 2000/2001, the oil price spike of 2008, and the 2008/2009 global financial crisis have undeniably and seriously undermined people's confidence in the ability of markets to adequately address important resource allocation issues.

    Opposition to the use of the price mechanism is particularly strong in the case of electricity. For instance, Blumsack and Lave (2006) have argued that the restructuring of the electricity sector has been a failure because of market manipulation. Van Doren and Taylor (2004) have also concluded that electricity restructuring has been a failure and that "vertical integration may be the most efficient organizational structure for the electricity industry." (Van Doren and Taylor, 2004, p. 9). And in a review of several restructuring studies, Kwoka (2008) adds his voice to the chorus of critics of the use of markets in the electricity sector. A recent challenge to this literature is provided by McDermott (2012) in a paper entitled, "The Regulatory Dilemma: Getting over the Fear of Price" in which the author makes the point that societal welfare is unlikely to be maximized when price signals are repressed. This challenge is buttressed by Craig and Savage (2013) who find that the increased competition associated with greater reliance on market forces increased the efficiency of investor-owned plants in the United States by about nine percent over the period 1996-2006.

    Regardless of one's views on the use of markets to allocate resources, the goals of electric power reliability and generation cost minimization are facilitated by having highly accurate dayahead forecasts of electricity demand. In a truly smart grid, system load would be known in advance with a high degree of confidence. This goal of "smart forecasting" is currently far from being realized. In the Pacific Gas and Electric (PG&E) aggregation zone managed by the California Independent System Operator (ISO), the root mean squared forecast error was approximately 450 MW over the period 1 April 2009 through 31 March 2010 corresponding to about 3.8 percent of average load. This error level may appear small except for the inconvenient fact that the stability of the power system requires that the supply of electricity match demand at all times, not merely on average.

    One of the load forecasting challenges for the California ISO is the "Delta Breeze" phenomenon (SIO and SAIC, 2004), a sea breeze that carries cool air from the ocean into the San Francisco Bay area and up to 100 miles inland (SIO and SAIC, 2004, p. 15). The breeze is most prevalent between May and September when it generally lowers the cooling component of the electric load within the PG&E service territory. Its absence, however, can lead to a significantly higher electricity load. The California ISO has reported that the Delta Breeze is difficult to predict (SIO and SAIC, 2004, p. 27). Analyses of weather forecasts by NOAA confirm this view with the forecast errors (forecasted temperatures minus actual temperatures) being systematically positive when the Delta Breeze is blowing and systematically negative when it is not (SIO and SAIC, 2004, p. 11). Because electricity load is temperature sensitive, these errors have contributed to significant load forecasting errors. For example, on May 28 2003, the day-ahead forecasted load was 35,012 MW while the actual load was 39,577 MW. As a result, a stage 1 alert had to be declared (SIO and SAIC, 2004, p. 7).

    The California ISO is not the only balancing area to experience significant load forecasting errors. Preliminary analyses of the load forecast errors for the French Power Grid (http://www.rtefrance. com), the New York Independent System Operator (http://www.nyiso.com), and the PJM Regional Transmission Organization (http://www.pjm.com) reveal that the day-ahead load forecast errors in these balancing areas are nontrivial as well. For example, over the period 1 January 2000 through 31 December 2008, approximately 16 percent of the days in New York City, the New York Independent System Operator's leading zone in terms of electricity consumption, had a root-mean-day-ahead-forecast-error in excess of five percent of daily mean load. In the case of the French power grid, over the period 1 November 2003 through 31 December 2007, approximately seven percent of the days in France had a root-mean-day-ahead-forecast-error in excess of five percent of daily mean load.

    This paper assesses the efficiency of markets with what we think is a novel test of the informational content of day-ahead electricity prices. Following Bachelier (1900), the first to recognize what has become known as the efficient market hypothesis, we begin with the proposition that if day-ahead markets for electricity are efficient, then day-ahead prices will reflect the load forecast generated by the system operator as well as the information processed by and the consequent insights of all market participants. For example, suppose a system operator has failed to account for the effect of a holiday in its load forecast but that market participants know that the holiday in question will boost demand. The market participants will incorporate the holiday induced demand into their economic calculations and thus the impact of the holiday on electricity demand will be reflected in the day-ahead prices. Consequently, to the extent that there are many of these holidays, load and day-ahead prices will be correlated. More importantly, if the market is efficient, the day-ahead prices will reflect all available meteorological information including the forecasts by any proprietary models that are more accurate than that employed by the system operator. Hence, one can hypothesize that if day-ahead prices accurately reflect the processed information and expectations of all market participants regarding day-ahead demand, then the prices will be useful...

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