Electricity market analytics for risk management purpose

Abstract

The pricing of electricity is central to the market, and forecasting future electricity prices is a matter that market participants cannot avoid dealing with. Due to the special characteristics of electricity, electricity prices are influenced by many factors and show high volatility and uncertainty, which brings great challenges to the accurate prediction of electricity prices. To improve prediction accuracy and efficiency, the actual measurement data of the Singapore electricity market is used for a case study to forecast the electricity price of next week with KNN, SVM and BPNN. By comparing their results, we can see the performance of the each to forecast electricity price, which is meaningful to risk management.