EEM 2017 Forecast Competition : Wind power generation prediction using autoregressive models

Energy forecasting provides essential contribution tointegrate renewable energy sources into power systems. Today,renewable energy from wind power is one of the fastest growingmeans of power generation. As wind power forecast accuracygains growing significance, the number of models used forforecasting is increasing as well. In this paper, we propose anautoregressive (AR) model that can be used as a benchmarkmodel to validate and rank different forecasting models andtheir accuracy. The presented paper and research was developedwithin the scope of the European energy market (EEM) 2017wind power forecasting competition.QC 20170801