Photovoltaic Model Identification Using Particle Swarm Optimization With Inverse Barrier Constraint 论文

摘要

The photovoltaic (PV) model is used in simulation studies to validate system design such as the maximum power point tracking algorithm and microgrid system. It is often difficult to simulate a PV module characteristic under different environmental conditions due to the limited information provided by the manufacturers. In this paper, a new approach using particle swarm optimization (PSO) with inverse barrier constraint is proposed to determine the unknown PV model parameters. The proposed method has been validated with three different PV technologies and the results show that the maximum mean modeling error at maximum power point is less than 0.02% for P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mp</sub> and 0.3% for V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mp</sub> .