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Electricity Demand and Price Analysis in California Using Possibility Regression Model
Osamu Hirano*, Masayasu Kanke**, and Kazuhiro Ozawa***
*Graduate School of Social Sciences, Hosei University, 4342 Aihara-machi, Machida-shi, Tokyo 194-0298, Japan
**Meidensha Corporation, 127, Nishishin-machi, Ohta-shi, Gunma 373-0847, Japan
***Institute of Comparative Economic Studies, Hosei University, 4342 Aihara-machi, Machida-shi, Tokyo 194-0298, Japan
Received:February 2, 2003Accepted:February 24, 2003Published:June 20, 2003
Keywords:possibility regression analysis, fuzzy number, spot price of deregulated electricity market, forecasting
Abstract
In this paper, the authors analyze the prices of electricity spot market in California. Firstly, we discuss the relation between annual demand of electricity and the temperature in California. We identify the electricity demand is related to temperature using possibility regression analysis. Then we show the fluctuation of electricity price is influenced by the demand. In the early summer season of 1998, the relationship between temperature and electricity price in California was simple. However, in the mid summer season in 1998, the price volatility of the electricity goes on increasing. Secondly we show that the expectation (speculative buying) of the market participant which is formed by temperature fluctuation induced the price volatility. We show that the price volatility is affected by temperature fluctuation for a previous few days.
Cite this article as:O. Hirano, M. Kanke, and K. Ozawa, “Electricity Demand and Price Analysis in California Using Possibility Regression Model,” J. Adv. Comput. Intell. Intell. Inform., Vol.7 No.2, pp. 147-152, 2003.Data files:
