Multi-time scale game dispatching strategy for microgrid cluster with shared energy storage considering demand response uncertainty

Abstract

Integrating a high proportion of renewable energy causes severe power fluctuations in microgrid clusters, and the uncertainty of demand response (DR) on the user side effects the optimal scheduling accuracy of the microgrid cluster. The cooperative operation of shared energy storage (SES) and microgrid cluster can effectively suppress microgrid power fluctuations and reduce the operating costs of independently configured energy storage for microgrid clusters. To effectively reduce the microgrid cluster's operating costs and power fluctuations and achieve mutual benefits for the microgrids and the SES, the paper proposes a multi-time scale game dispatching strategy of the SES and the microgrids with the uncertainty of demand response. Firstly, the uncertainty models for price-based and incentive-based demand responses are established based on the Logistic function and fuzzy chance constraints, respectively. This approach aims to enhance the modeling accuracy of user response behavior and reduce the impact of modeling errors on scheduling plans. Secondly, considering the multi-time scale characteristic and uncertainty of user-side demand response, a multi-time scale master-slave game optimization dispatching model is developed. In this model, the SES operator acts as the leader in adjusting the capacity leasing price and charging-discharging price dynamically, and each microgrid acts as the follower in optimizing the rental capacity and charging-discharging strategy. The model is solved using an adaptive particle swarm algorithm integrated with the CPLEX solver to enhance the accuracy of the dispatching plan. Finally, the performance of the proposed strategy is verified through case analysis. The results demonstrate that the proposed model can reduce energy costs and power fluctuations of microgrids more effectively than the traditional single-timescale scheduling model and realize the mutual benefits for microgrids and SES.