8th International Conference on Advanced Power System Automation and Protection (APAP2019)

931 / 2019-04-30 17:43:37

Multi-Scene Parameter Identification of Photovoltaic Array Based on Multi-Objective Adaptive Particle Swarm Optimization

Photovoltaic array; Parameter identification; Multi-objective adaptive particle swarm optimization algorithm; Root mean square error function; Multi-scenario

Based on the single diode equivalent circuit model of photovoltaic cells and the I-U output characteristic equation, a parameter identification method of multi-objective adaptive particle swarm optimization (MO-SAPSO) is proposed. By introducing the adaptive inertia weight operator ω, the global search ability and local search ability of the algorithm can be balanced, making the algorithm not easy to produce premature phenomenon. According to the difference between the measured output current of the photovoltaic array and the theoretical calculated current, considering the influence of environmental changes on internal parameters, a root-mean-square error function was constructed to transform the complex multi-parameter identification problem into a nonlinear multi-variable optimization problem with constraints. Finally, the multi-scene method is adopted to verify the applicability and effect of the algorithm under different illumination intensity and temperature. The simulation results show that the algorithm is superior to other algorithms in error, convergence speed and running time.