Modelling the Evolution of Wind and Solar Power Infeed Forecasts

With the increasing integration of wind and photovoltaic power in the whole European power system, there is a longing for detecting how to trade energy in the ever-changing intraday market from electric power industries. The intraday trading becomes even more relevant in the wake of the European Cross-Border Intraday (XBID) project, which aims at integrating the electricity trading cross Europe. Therefore, optimal trading strategies to address renewables output forecast fluctuations are growingly required to be designed. In this study, we model, simulate and predict the evolution of wind and PV infeed forecasting errors updated every 15-minute, which participants in the intraday market typically incorporate in the adjustments of price bids. We employed several stochastic and probabilistic models and found a superior performance of the later to accurately predict 15-minute renewable forecasts. Since ex-ante updated forecasting errors of renewables infeed are usually not available to researchers, simulations based on our proposed models break the ground for further applications to intraday pricing and optimization