Based on the niche idea and the catastrophe theory, a new particle swarm optimization algorithm is suggested in this paper, which can adaptively adjust the swarm grouping. This algorithm proposes that, after obtaining local optimal area, only parts of the particles are left to find local optimal point, while other particles are dealt with by catastrophe, and are restrained in the remaining regions for new search. In this way, the particle swarm can not only improve the convergence rate and precision, but also effectively enhance the ability of global optimization. Therefore, this new algorithm can be applied to predict the maximum power point (MPP) of the photovoltaic cell. Meanwhile, the effectiveness of this algorithm is demonstrated in the experimental findings.
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