Statistical analysis of electricity demand and spot prices in competitive markets

Michalik, Grazyna; Khan, M.E.; Mielczarski, W.

doi:10.1049/cp:19971877

Cited by 3 publications

(1 citation statement)

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“…Traditional methods based on statistical and probabilistic approaches may not be suitable to represent data generated by human activities such as the prices in the power exchange market. For example, market-based transactions of electricity tend to make prices more volatile in the high demand region than in the low demand region, depreciating the traditional assumption of random process [7].…”

Section: Introductionmentioning

confidence: 99%

Electricity Price Prediction Model Based on Simultaneous Perturbation Stochastic Approximation

Ko¹,

Lee²,

Kim³

2008

Journal of Electrical Engineering and Technology

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-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 PennsylvaniaNew Jersey-Maryland (PJM) electricity market.

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Section: Introductionmentioning

confidence: 99%