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A comprehensive survey of the application of swarm intelligent optimization algorithm in photovoltaic energy storage systems.
Wang, Shuxin; Yue, Yinggao; Cai, Shaotang; Li, Xiaojuan; Chen, Changzu; Zhao, Hongliang; Li, Tiejun.
Afiliación
  • Wang S; School of Intelligent Manufacturing, Shanghai Zhongqiao Vocational and Technical University, Shanghai, 201514, China.
  • Yue Y; School of Intelligent Manufacturing and Electronic Engineering, Wenzhou University of Technology, Wenzhou, 325035, China.
  • Cai S; Information and Communication Branch, State Grid Chongqing Electric Power Company, Chongqing, 400014, China. caishaotang1992@163.com.
  • Li X; School of Intelligent Manufacturing and Electronic Engineering, Wenzhou University of Technology, Wenzhou, 325035, China. lixiaojuan9889@163.com.
  • Chen C; School of Intelligent Manufacturing and Electronic Engineering, Wenzhou University of Technology, Wenzhou, 325035, China.
  • Zhao H; Zhejiang Carspa New Energy., LTD, Wenzhou, 325035, China.
  • Li T; Zhejiang Carspa New Energy., LTD, Wenzhou, 325035, China.
Sci Rep ; 14(1): 17958, 2024 Aug 02.
Article en En | MEDLINE | ID: mdl-39095569
ABSTRACT
With the rapid development of renewable energy, photovoltaic energy storage systems (PV-ESS) play an important role in improving energy efficiency, ensuring grid stability and promoting energy transition. As an important part of the micro-grid system, the energy storage system can realize the stable operation of the micro-grid system through the design optimization and scheduling optimization of the photovoltaic energy storage system. The structure and characteristics of photovoltaic energy storage system are summarized. From the perspective of photovoltaic energy storage system, the optimization objectives and constraints are discussed, and the current main optimization algorithms for energy storage systems are compared and evaluated. The challenges and future development of energy storage systems are briefly described, and the research results of energy storage system optimization methods are summarized. This paper summarizes the application of swarm intelligence optimization algorithm in photovoltaic energy storage systems, including algorithm principles, optimization goals, practical application cases, challenges and future development directions, providing new ideas for better promotion and application of new energy photovoltaic energy storage systems and valuable reference.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido