Optimal two-stage arbitraging and scheduling strategy for distributed energy resource aggregators

Given the rapid development of the distributed energy resources (DER), involving DERs into the wholesale market under the market and renewable uncertainties to achieve economic benefits is necessary but challenging. In this work, an arbitraging strategy is proposed for DER aggregators that bridge DERs with the wholesale market through energy trading. Besides, a novel self-adaptive minimax regret (MMR)-based optimal offering model is proposed for the DER aggregator to handle the uncertainties in both renewable generations and market prices. Additionally, an exact and communication-free solution methodology is proposed to resolve the formulated optimization problem with high computational efficiency. In the numerical results, the proposed methods can achieve near-to-optimal profits. Moreover, the performance of the proposed approach remains satisfactory even if the environment becomes very volatile.