Electricity Price Prediction Model Based on Simultaneous Perturbation Stochastic Approximation

  • Ko, Hee-Sang (Wind Energy Research Center, Korea Institute of Energy Research) ;
  • Lee, Kwang-Y. (Dept. of Electrical and Computer Engineering, Baylor University) ;
  • Kim, Ho-Chan (Dept. of Electrical Engineering, Cheju National University)
  • 발행 : 2008.03.01


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.


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