Do Electricity Prices Reflect Economic Fundamentals?: Evidence from the California ISO

نویسندگان

  • Kevin F. Forbes
  • Ernest M. Zampelli
چکیده

In a truly smart grid, system load would be known in advance with a high degree of confidence. Currently, this goal of “smart forecasting” is far from being realized. In the Pacific Gas and Electric (PG&E) aggregation area managed by the California Independent System Operator (ISO), the root mean squared day-ahead forecast error was about 3.8 percent of mean actual load over the period 1 April 2009 through 31 March 2010. This error may appear small except for the inconvenient fact that the stability of the power system requires that electricity demand and supply of electricity match at all times, not merely on average. This paper contends that if day-ahead markets for electricity are efficient, then day-ahead prices will reflect the load forecast generated by the system operator along with the information processed by and the consequent insights of all market participants. For example, suppose a system operator fails 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 so that the impact of the holiday on electricity demand will be reflected in the day-ahead prices. Consequently, one can hypothesize that if day-ahead prices reflect the processed information and expectations of all market participants regarding day-ahead demand, then the day-ahead prices may be useful in predicting load. We test this hypothesis using data for the PG&E aggregation area in the California ISO. Variations in load can be accounted for by the day-ahead hourly price relative to the price of natural gas, natural gas being one of the primary fuels used to produce electricity in California. Evidence is presented that the root-mean-squared errors of the day-ahead load forecasts can be significantly reduced when the load forecasts are modified using the day-ahead information.

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تاریخ انتشار 2012