Sample-Oriented Electricity Storage Sharing Mechanism Design With Performance Guarantees

Sharing economy is believed to be able to improve the efficiency of the electricity sector by sharing the underutilized electricity storage. However, this is a delicate task because the optimal decision making often requires the distributional information of demand, which is often hard to obtain and characterize. Hence, the decision making has to rely on the historical samples. While the literature has investigated the sample-based storage control, little is known about historical samples' theoretical impact on the storage sharing performance. To this end, we theoretically conduct the performance analysis for the sample-based storage sharing decisions. To highlight the impact of the samples, we consider two kinds of historical samples: one is pure demand information, and the other is additionally associated with external feature information. We investigate how these two kinds of samples enable the decision making with a performance guarantee. We further compare the theoretical performance bounds with the empirical results, indicating the effectiveness of the proposed methods and the tightness of the derived bounds. Our theoretical analysis provides a new perspective for efficient demand sample collection and cost-effective sharing mechanism design.