福州大学学报（自然科学版）2017，Vol.45Issue(1)：108-114,7.DOI:10.7631/issn.1000-2243.2017.01.0108
改进多种群粒子群算法辨识光伏组件参数
Photovoltaic module parameters identification using an improved multi-group particle swarm optimization algorithm
摘要
Abstract
Addressing the issue of photovoltaic module parameters identification,a new hybrid algorithm based on multi-group particle swarm optimization and simplex method is proposed.Firstly,the transcendental equation of the single diode photovoltaic model is modified so as to greatly reduce the computation complexity.Secondly,the search space for the parameters is optimized by pre-estimating the parameters initial value.And then,combining the advantage of multi-group particle swarm optimization and simplex method,a hybrid N-MPSO algorithm is constructed to quickly obtain the stable and accurate parameters.Finally,the algorithm is validated by several groups of Ⅰ-V data measured from some typical photovoltaic modules.The results show that the proposed N-MPSO algorithm can reach a higher accuracy and lower time complexity compared with some other conventional methods,which is significant to the design,testing and diagnosis of photovoltaic modules and power stations.关键词
光伏组件/参数辨识/N-MPSO算法Key words
PV module/parameter identification/N-MPSO algorithm分类
信息技术与安全科学引用本文复制引用
吴越,陈志聪,吴丽君,林培杰,程树英,陆培民..改进多种群粒子群算法辨识光伏组件参数[J].福州大学学报（自然科学版）,2017,45(1):108-114,7.基金项目
国家自然科学基金资助项目(51508105 （）
61601127) （）
福建省自然科学基金资助项目(2015J05124) （2015J05124）
福建省科技厅高校产学合作资助项目(2016H6012) （2016H6012）
福建省教育厅产学研资助项目(JA14038) （JA14038）
福建省科技厅工业引导性重点资助项目(2015H0021) （2015H0021）
福建省经信委省级技术创新重点资助项目(830020) （830020）
