With the continuous increase in the penetration rate of distributed photovoltaics

traditional photovoltaic modeling methods are no longer able to meet modeling needs. To establish a model for large-scale regional distributed photovoltaic systems and study their operational characteristics

a dynamic clustering multi-machine equivalent modeling method for distributed photovoltaic power generation systems is proposed. Firstly

representative feature points of the fault curve are selected as clustering indicators. Then

based on the improved FCM (fuzzy-C means) clustering algorithm

the distributed photovoltaic systems in the region are clustered using the selected feature points as indicators. Subsequently

the parameters design of the equivalent model is carried out. For control parameters that are difficult to obtain

a multi-objective optimization algorithm based on NSGA-II (non-dominated sorting genetic algorithm II) and principal component analysis is used to identify them. Other parameters are obtained using capacity weighting method. Thus a multi-machine equivalent model for regional distributed photovoltaic systems is constructed. Finally

the feasibility and accuracy of the proposed equivalent modeling scheme of distributed photovoltaic equivalent model is significantly improved using Simulink simulation tools.