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考虑目标分解及其互补平抑的风电场复合储能容量优化 被引量:22

Capacity Optimization of Hybrid Energy Storage System Based on Target Decomposition and Complementary Fluctuations Smoothing
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摘要 融合多种储能介质优质特性的复合储能将是未来储能技术发展的重要方向。以具备规模化应用可行性的铅酸蓄电池(VRLA)与全钒液流电池(VRB)为例,针对复合储能系统研究了其容量优化配置计算方法。首先,针对复合储能系统介质特性分解平抑功率目标;其次,构建发挥各介质优势且可协调优化的复合系统充放电策略;最后,建立以复合储能系统经济性运行为目标函数的容量优化配置模型,并基于粒子群优化(PSO)算法实现了求解计算。某风电场实际运行数据分析结果表明,经文中方法优化配置的复合储能系统在等效运行成本、平抑效果、充放电次数等方面均得到了优化,验证了该方法的有效性。 Hybrid energy storage system(ESS)has multiple advantages and leads to an important ESS research direction in the future.Take valve regulated lead acid(VRLA)battery and vanadium redox battery(VRB)hybrid ESS as an example,which has massive application feasibility,a novel capacity optimization method for hybrid ESS is proposed.Firstly decompose fluctuation smoothing target according to different ESS medium;secondly construct charge and discharge strategy for both independent and complementary fluctuation smoothing;finally develop capacity optimization modeling taking economic operation as objective function,and realize calculation based on particle swarm optimization(PSO)algorithm.The actual wind farm power data shows that this method can optimize the hybrid ESS on equivalent running cost,smoothing effects,charge or discharge times,and has high validity.
出处 《电力系统自动化》 EI CSCD 北大核心 2014年第7期9-15,共7页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(51307101 51177091) 山东省优秀中青年科学家科研奖励基金资助项目(BS2013NJ011) 国家高技术研究发展计划(863计划)资助项目(2011AA05A101)~~
关键词 风电场 复合储能 储能容量 粒子群优化 容量优化 wind farm hybrid energy storage system energy storage capacity particle swarm optimization (PSO) capacity op timization
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