The short term electricity prices forecasting using Markov chains

This paper presents a method for short-term electricity price forecasting based on combination of the Monte Carlo simulation and Markov chains. The method provides an estimation of the probabilities of various electricity price ranges, average prices, and probabilities of the highest price range, for each hour of the next 24 hours. The external variables have been implicitly accounted for through the Monte Carlo simulation. Using the market data of the European Power Exchange (EPEX) as a test case, the effectiveness of the proposed method has been verified by comparison with the best regression methods.