Collaborative optimal scheduling of shared energy storage station and building user groups considering demand response and conditional value-at-risk

Energy storage devices can improve the utilization of clean energy and reduce the operating costs of building users. However, traditional energy storage is limited by its relatively low resource utilization and high cost. Firstly, to fully utilize the advantages of energy storage, a shared energy storage station (SESS) is introduced into the building user groups (BUGs). Second, this paper considers the incentive effect of flexible load participation in demand response (DR) on BUGs, quantifies the risky scheduling cost of wind uncertainty using conditional value-at-risk (CVaR), and then proposes a collaborative optimal scheduling model for BUGs and SESS considering DR and CVaR. Finally, the proposed model is verified by examples to achieve efficient complementation of SESS and BUGs, reduce the risk scheduling cost due to wind power uncertainty, and significantly reduce the capacity value of SESS and the electricity purchase of BUGs; meanwhile, this study carries out multi-perspective sensitivity analysis and CVaR analysis,which is informative for the refinement of the operating model of SESS and BUGs.