Translated Title
Photovoltaic module parameters identification using an improved multi-group particle swarm optimization algorithm
Translated 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.
Translated Keyword
N-MPSO algorithm
parameter identification
PV module
Access Number
WF:perioarticalfzdxxb201701018
