The present paper proposes a novel methodology for the optimisation of energy storage allocation strategies within wind-solar storage microgrid systems. Firstly, a framework for the joint optimization and configuration of photovoltaic power generation, energy storage, and the power grid within the park has been developed. Secondly, the optimal energy storage allocation strategy for the wind-solar-storage microgrid system is determined based on the particle swarm algorithm (PSO). The potential of collaborative scheduling in joint parks is then verified by comparing the self-sufficiency of power supply in independent parks. The optimal energy storage configuration scheme for A park without energy storage configuration, B, C, and D parks with 153.81kW/400.13kWh, 54.74kW/68.42kWh, and 83.7kW/200kWh, was ultimately determined. It reveals the operation law of the joint operation mode to realize the optimal system operation through the energy sharing mechanism.

Yangyao Li. Coordinated Optimization Configuration of Park Microgrid Wind-Solar-Storage. International Journal of New Developments in Engineering and Society (2025), Vol.9, Issue 2: 33-40. https://doi.org/10.25236/IJNDES.2025.090206.

[1] Chunhui Qu, Xiangwen Zhang, Shuwu Hu, et al.Research and Engineering Field-test of a Renewable Energy Stations Rapid Power Control Technology for Improving Power Grid Stability[C]// 2021 International Conference on Power System Technology (POWERCON).IEEE,2021:1-8. 

[2] G. Sultana and B. K. Keshavan. Evaluation of Performance and Reliability Indices of a Micro-Grid with Distributed Generation[C].2020 IEEE REGION 10 CONFERENCE (TENCON).IEEE, 2020: 341-346.

[3] Yifan Ding, Feifei Sun, Chenrui Duanmu,et al. Optimized operation strategy of pumped storage-electrochemical energy storage for renewable energy consumption [C]// 2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA).IEEE,2024:670-675.

[4] Zhang Jinyuan. The optimization model of wind-optical co-storage configuration for campus microgrid based on improved particle swarm optimization algorithm[C]//2024 IEEE 2nd International Conference on Electrical, Automation and Computer Engineering(ICPECA).IEEE,2024:615-618.

[5] MA Yuxin, HU Zechun, DIAO Rui. Day-ahead Optimization Strategy for Shared Energy Storage of Renewable Energy Power Stations to Provide Frequency Regulation Service[J]. Power System Technology, 2022,46(10):3858-3868.

[6] MA Xiaoguo. Development and Challenges of Distributed Generation,Microgrid and Smart Distribution Network[J]. Telecom Power Technology,2018,35(8):271-272.

[7] Yang M , Chen C , Que B ,et al.Optimal Placement and Configuration of Hybrid Energy Storage System in Power Distribution Networks with Distributed Photovoltaic Sources[C]//2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2).IEEE, 2018. DOI:10.1109/EI2.2018.8582007.

[8] LIU Shu, ZHAO Chuang,ZOU Wenguang et al. Coordinated Optimization Configuration of Park Microgrid Wind-Solar-Storage Based on MILP[J]. NORTHEAST ELECTRIC POWER TECHNOLOGY, 2024 45(12):5-10.

[9] PENG Sui, GONG Xianfu, LIU Xinmiao et al. Optimized Energy Storage Configuration of Wind Power Integrated Power System Considering DC Regulation Capacity[J]. ELECTRIC POWER,2022 5(1),37-45.

[10] Yuhua Tan, Qian Zhang, Chen Li, et al. An Improved Modeling Method for Uncertainty of Renewable Energy Power Generation Considering Random Variables Correlation[C]. 2022 7th Asia Conference on Power and Electrical Engineering (ACPEE).IEEE,2022:84-89.