Logistic quantum-behaved particle swarm optimization based MPPT for PV systems

Partial shading of photovoltaic cells would happen frequently during power generation process. With the result that output power-voltage (PV) characteristic curve of PV arrays could result in multiple power peaks, the traditional technology of maximum power point tracking (MPPT) control algorithms will be failure. Based on this situation, this article mainly proposed a MPPT(maximum power point tracking) algorithm based on a Logistic Quantum-behaved Particle Swarm Optimization (LQPSO) and Incremental Conductance method to get the maximum power and fast convergence of PV arrays, by adjusting the duty cycled of power switching to control the value of the output power. The MATLAB/Simulink is adopted to evaluate the effectiveness of the proposed algorithm, and the simulation results prove our algorithm has the ability to track the maximum power point in an extreme environmental condition.