Energy Storage Capacity Configuration and Scheduling Method for Microgrid Considering Demand Response

Tingzhe Pan (), Chao Li, Xin Jin, Zijie Meng and Xinlei Cai
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Tingzhe Pan: Electric Power Research Institute, China Southern Power Grid Company Limited, Guangzhou 510000, China
Chao Li: Power Dispatch Control Center, Guangdong Power Grid Limited, Guangzhou 510663, China
Xin Jin: Electric Power Research Institute, China Southern Power Grid Company Limited, Guangzhou 510000, China
Zijie Meng: Power Dispatch Control Center, Guangdong Power Grid Limited, Guangzhou 510663, China
Xinlei Cai: Power Dispatch Control Center, Guangdong Power Grid Limited, Guangzhou 510663, China

Energies, 2025, vol. 18, issue 19, 1-15

Abstract: In recent years, with the development of the electricity market, electricity users have also been able to participate in electricity trading. The energy storage capacity configuration of microgrids with renewable energy considering demand response is of great significance for reducing microgrid costs, improving renewable energy consumption levels, and enhancing microgrid performance. This study first establishes a microgrid model considering demand response. Constraints and economic models of the microgrid are then provided to obtain the cost of the microgrid. To identify the energy storage capacity and the energy scheduling strategy that minimizes the operation cost of the microgrid, this study proposes a two-layer optimization model. The inner layer uses solvers to optimize the transferable loads, interruptible loads, and the energy storage power under the demand response mechanism to minimize the short-term cost. The outer layer uses the particle swarm optimization (PSO) algorithm to optimize the energy storage capacity and minimize the long-term cost. A case analysis shows that the demand response mechanism and reasonable energy storage configuration have a significant effect on reducing the operation cost of the microgrid. In addition, energy storage can reduce power fluctuations in connecting lines and improve the stability of the microgrid.

Keywords: demand response; microgrid; energy storage; particle swarm optimization; capacity configuration (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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