A Complex-Method-Based PSO Algorithm for the Maximum Power Point Tracking in Photovoltaic System

In order to deal with problems of premature convergence and slow convergence rate, this paper proposes a Complex-method-based Particle Swarm Optimization algorithm, namely CPSO. At the beginning of the evolution, the PSO is applied to implement global search, and when the group of particles has entered into the local optimum region, the Complex method is used to quickly get the local optimal point, which can effectively improve the ability of local search. The mutation inertia weight is also used in the CPSO to jump out of the local optimum, which can increase the diversity of the population and solve the premature convergence problem. This new algorithm is applied for the maximum power point tracking (MPPT) in the photovoltaic system, and the effectiveness of this algorithm is demonstrated in the experimental findings.