Evaluation of Wind Energy Forecasts: the Undervalued Importance of Data Preparation

Abstract

The evaluation of wind energy forecasts is a key task for those involved in the wind power sector, and the accurate evaluation of forecasts is fundamental to make informed decisions both in business and research. To evaluate the accuracy of a forecast, observed values must be compared against forecast values over a test period. At times, however, the actual generation of a wind farm can be affected by factors that are outside the scope of the forecast model. Evaluating a forecast using a data set that includes such out-of-scope observations might give a biased or inconsistent assessment. In the data preparation phase, then, the evaluator should identify out-of-scope data and decide whether to include or remove these from the data set. In this paper, we carry out an empirical study based on data from an existing wind farm and a number of day-ahead forecasts in order to highlight the effects of including in- and out-of-scope data on forecast accuracies. The results show that the outcome of the evaluation varies significantly depending on the criteria adopted in the data selection.