Paper
27 September 2024 An analysis method of mutual regulation potential of water-light-storage cluster based on mixed integer programming and mathematical model
Xuan Xu, Han Cheng, Chao Fang, Zhanglei Zheng, Ruisheng Diao
Author Affiliations +
Proceedings Volume 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024); 132810E (2024) https://doi.org/10.1117/12.3051330
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning, 2024, Zhengzhou, China
Abstract
In order to reduce the power generation load of water-light-storage cluster and ensure the balance between energy storage and power supply, the mixed integer programming and mathematical model are introduced, and an analysis method of mutual regulation potential of water-light-storage cluster is designed. The overall structure of water-light-storage cluster microgrid is designed, and the mathematical models of hydro-generator set, photovoltaic power supply and energy storage battery are constructed. On this basis, the analysis characteristics of mutual regulation potential of water-light-storage cluster are extracted and analyzed, and the potential analysis is realized under mixed integer programming. The experimental results show that the power output of water-light-storage cluster mutual regulation becomes significantly more stable after the application of this method, and the load of hydro-generator, photovoltaic power supply and energy storage battery shows relatively stable values, which is more effective in optimizing cluster mutual regulation and can distribute and balance the load of various energy sources more reasonably.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xuan Xu, Han Cheng, Chao Fang, Zhanglei Zheng, and Ruisheng Diao "An analysis method of mutual regulation potential of water-light-storage cluster based on mixed integer programming and mathematical model", Proc. SPIE 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024), 132810E (27 September 2024); https://doi.org/10.1117/12.3051330
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KEYWORDS
Solar energy

Mathematical modeling

Batteries

Solar cells

Computer programming

Power supplies

Photovoltaics

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