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Electricity Price Prediction Model Based on Simultaneous Perturbation Stochastic Approximation
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 Title & Authors
Electricity Price Prediction Model Based on Simultaneous Perturbation Stochastic Approximation
Ko, Hee-Sang; Lee, Kwang-Y.; Kim, Ho-Chan;
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 Abstract
The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.
 Keywords
electricity market;intelligent time series;price prediction;simultaneous perturbation stochastic approximation;
 Language
English
 Cited by
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