Forecasting electricity spot prices using time-series models with a double temporal segmentation

摘要

The French wholesale market is set to expand in the next few years underEuropean pressure and national decisions. In this paper, we assess the forecasting abilityof several classes of time series models for electricity wholesale spot prices at a day-aheadhorizon in France. Electricity spot prices display a strong seasonal pattern, particularly inFrance given the high share of electric heating in housing during winter time. To deal withthis pattern, we implement a double temporal segmentation of the data. For each tradingperiod and season, we use a large number of specifications based on market fundamentals:linear regressions, Markov-switching models, threshold models with a smooth transition.An extensive evaluation on French data shows that modeling each season independentlyleads to better results. Among non-linear models, MS models designed to capture thesudden and fast-reverting spikes in the price dynamics yield more accurate forecasts.Finally, pooling forecasts gives more reliable results.