A selection of time series models for short- to medium-term wind power forecasting

In this paper we investigate the short- to medium-term prediction performance of several recent wind power forecasting models. In particular, we analyze the Wind Power Prediction Tool (WPPT), which is a successfully employed model in Denmark, its generalization (GWPPT, generalized WPPT), an adaptation of the Mycielski approach, a nonparametric regression model and several univariate time series benchmarks. In the longer forecasting horizon scenario, GWPPT performs best, while the time series models are still strong competitors in the short-term setup. Our findings are in line with the majority of the literature. They support the results by Croonenbroeck and Dahl (2014). The Mycielski approach is a successfully employed wind speed forecaster and usually returns well results. However, its performance as a wind power forecasting model is somewhat limited, showing that the adaptation to this new operational area leaves an opportunity for additional work in the future.