Optimal Energy Storage System Operation Model for Peak Reduction with Prediction Uncertainty

Abstract This study is aimed at determining the optimal energy storage system (ESS) operation schedule to minimize the peak load on the feeder of a distribution network. To reduce the peak load, the feeder load needs to be predicted. However, a deterministic prediction is not reliable because it may contain errors. This study proposes the use of the prediction interval (PI) of the error estimated based on prior predictions. An algorithm is used to determine the optimal ESS schedule using the PI. To demonstrate the method’s validity, a case study is presented, where the proposed optimal ESS schedule determined based on PI reduces the peak load during network operations over a one-year period. The performance of the proposed method is superior to that of the conventional method which uses deterministic load prediction.