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文章摘要
基于改进粒子群算法的混合储能系统容量优化
Capacity Optimization of Hybrid Energy Storage Based on Improved PSO Algorithm
Received:October 10, 2014  Revised:October 10, 2014
DOI:
中文关键词: 风光互补发电系统  超级电容器  混合储能  粒子群算法  加速因子
英文关键词: wind-solar generation system  ultracapacitor  hybrid energy storage  PSO  acceleration coefficient
基金项目:国家自然基金项目
Author NameAffiliationE-mail
Yang Guo-hua* Department of Electrical Engineering and Automation,Ningxia University ghyangchina@126.com 
Zhu Xiang-fen Department of Electrical Engineering and Automation,Ningxia University  
Ma Yu-juan Department of Electrical Engineering and Automation,Ningxia University  
韩世军 Department of Electrical Engineering and Automation,Ningxia University  
Wei Ning-bo Department of Electrical Engineering and Automation,Ningxia University  
wangpengzhen ningxia university  
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中文摘要:
      为了调高风光互补发电储能系统的经济性减少其运行费用,研究风光互补发电储能系统的容量优化配置模型,提出一种改进粒子群算法的混合储能容量优化方法。首先通过对全生命周期费用静态模型的介绍,以蓄电池和超级电容器作为风光互补系统混合储能装置,以其全生命周期费用最小为目标,以系统的缺电率等运行指标为约束条件,建立了一种混合储能系统容量优化配置模型,其次改进设计了加速因子,提出了改进的粒子群算法,最后利用算例在Matlab中进行了仿真与求解。仿真结果表明,该方法不仅优化了蓄电池的工作状态,降低了储能系统的全生命周期费用,而且加快了收敛速度。
英文摘要:
      To solve the problem of optimal allocation of energy storage system, in this paper, we presented a hybrid energy storage capacity optimization method by improving PSO Algorithm. A hybrid energy storage capacity optimization model has been constructed, which considers battery and ultracapacitor as a hybrid energy storage device, considers the lowest annual life cycle cost of hybrid energy storing device as the optimization objective, and considers the indices such as the loss of power supply probability as constrain conditions. Then solves the problem with acceleration coefficient improved PSO algorithm, and simulates the case using Matlab. The simulation result shows that the method not only can optimize the work condition of the battery, reduce the cost of the energy storage system and the life cycle cost, but can improve the convergence speed.
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