An Effective Approach to Predicting Electricity Market Price Spikes

Electricity market price prediction is important for market participants. The most of the predicting techniques are designed for normal price predictions other than price spikes predictions. The aim of this paper is to analyse electricity market data including demand, price, and capacity reserve, to find out their causes to the occurrence of price spikes. The challenge of spike prediction is the accuracy of the prediction that is on how a classifier can capture all spikes that would happen. Particularly precision/recall is used in the evaluation of the spike prediction. It has shown that ELM (Extreme Learning Machine) algorithm has a superior performance in prediction of price spikes compared with other existing classification algorithms such as SVM (Support Vector Machine). The experiments and the evaluation of the results have confirmed these findings.