2016 Volume 7 Issue 2 Pages 24-31
This paper considers application of a particle swarm optimization algorithm to the maximum power point tracking in photovoltaic systems. The cost function of a terminal voltage is time-variant in dynamic environment and the voltage corresponds to a particle. Since the terminal voltage can take one value at an instant, it is difficult to construct plural particles. In order to overcome this difficulty, our algorithm uses imaginary particles consisting of sampled values of the terminal voltage. In order to adapt to the dynamic cost function, the algorithm uses a flexible reset method of the personal best. In order to escape from a trap of local solution, the algorithm accelerates particles periodically. Performing basic numerical experiments, the algorithm efficiency is investigated.
