DocumentCode :
3220745
Title :
On the computation of the probability distribution of the spot market price in a deregulated electricity market
Author :
Valenzuela, J. ; Mazumdar, M.
Author_Institution :
Dept. of Ind. & Syst. Eng., Auburn Univ., AL, USA
fYear :
2001
fDate :
2001
Firstpage :
268
Lastpage :
271
Abstract :
In a deregulated electricity market, short- and long term decisions will be based on the spot price of electricity rather than on the load. The hourly spot prices of electricity have so far shown evidence of being highly volatile. In this paper, we propose a stochastic model for the spot market price of electricity in which no historical data for the prices are required. Rather than directly modeling the price, we model the underlying stochastic processes of the marginal unit that determines the price of electricity under market competition. The deregulated market of electricity is still evolving and the set of generating units participating in a particular market can be constantly changing. A model that uses historically observed market prices may thus give inaccurate predictions. Under these circumstances, it is very difficult to collect empirical data to obtain an accurate forecast for the spot market price. Our price model represents the market by a power generation system and captures its fundamental stochastic characteristics. This model highlights the dependence of the price on temperature fluctuations. The model is also used to provide analytical approximations to the bivariate probability distribution of the spot prices at two different hours
Keywords :
costing; electricity supply industry; power system economics; probability; stochastic processes; Monte Carlo; bivariate probability distribution; deregulated electricity market; electricity market competition; generating units; hourly spot prices; longterm decisions; marginal unit; power generation system; production costing models; short-term decisions; spot market price probability distribution; stochastic model; stochastic processes modeling; temperature fluctuations; Distributed computing; Economic forecasting; Electricity supply industry; Electricity supply industry deregulation; Power generation; Power system modeling; Predictive models; Probability distribution; Stochastic processes; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Industry Computer Applications, 2001. PICA 2001. Innovative Computing for Power - Electric Energy Meets the Market. 22nd IEEE Power Engineering Society International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6681-6
Type :
conf
DOI :
10.1109/PICA.2001.932360
Filename :
932360
Link To Document :
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