Research on capacity optimization of micro-grid hybrid energy storage system based on simulated annealing artificial fish swarm algorithm with memory function

被引：3
|
作者：
An, Yuan [1 ]
Li, Jianing [1 ]
Chen, Cenyue [1 ]
机构：
[1] Xian Univ Technol, Elect Engn, Xian 710048, Shaanxi, Peoples R China
来源：
2020 INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENT AND BIOENGINEERING (ICEEB 2020) | 2020年 / 185卷
关键词：
D O I：
10.1051/e3sconf/202018501023
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
The intermittence and uncertainty of wind power and photovoltaic power have hindered the large-scale development of both. Therefore, it is very necessary to properly configure energy storage devices in the wind-solar complementary power grid. For the hybrid energy storage system composed of storage battery and supercapacitor, the optimization model of hybrid energy storage capacity is established with the minimum comprehensive cost as the objective function and the energy saving and charging state as the constraints. A simulated annealing artificial fish school algorithm with memory function is proposed to solve the model. The results show that the hybrid energy storage system can greatly save costs and improve system economy.
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收藏
页数：6
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