Wind power generation benchmark analysis report

How to evaluate statistical wind power forecasting models?

Benchmarking framework to evaluate statistical wind power forecasting models. Standardized criteria in terms of data, time resolution and prediction horizon. Evaluation considering varied realistic operational conditions of wind farms. Example case applying the framework for very short-term prediction horizons.

Can performance evaluation methods be used to assess wind power forecast accuracy?

The present study gives an extensive overview of the performance evaluation methods used for assessing the forecast accuracy of short-term statistical wind power forecast estimates, and the concept of robustness is introduced to determine the validity of a model over different wind power generation scenarios over the testing set.

Are performance evaluation metrics robust under different conditions in wind power forecasting?

Finally, a numerical study using decomposition-based hybrid models is presented to analyse the robustness of the performance evaluation metrics under different conditions in the context of wind power forecasting. Data from Ireland are employed using two different resolutions to examine its influence on the forecast accuracy. 1. Introduction

Does wind power generation affect forecast accuracy?

None of the discussed studies goes into the limitations of evaluating WPFs, especially in terms of robustness, meaning that the forecast accuracy of a certain WPF model should not be affected by the wind power generation process, and therefore perform similarly for different scenarios of wind power generation .