The output of photovoltaic array was affected by the environmental factors such as irradiation and temperature, it was necessary to track the maximum power point of photovoltaic array. Aiming at shortage of the traditional particle swarm optimization algorithm for multi-objective optimization, multi-objective particle swarm optimization algorithm based on minimal particle angles was proposed, the globally optimal particle was updated by comparison of angles between different particles in the objective space; A method of updating locally optimal particles and swarm is presented based on particle densities. The maximum power point tracking method was established and simulated with Matlab/Simulink. Simulation results showed that the algorithm could rapidly and accurately track the maximum power point when the external environmental changed, and ensure the steady state characteristics of PV systems.

MPPT Control Method of PV System with PSO Algorithm Based on Minimal Particle Angles

The limit set of elementary cellular automaton is found through defining some kinds of particles and its regularity is proved.The result shows that the finite automaton can accept this limit set.

Qin Da-kang

Papers

Limit Language Complexity of Elementary Cellular Automation of Rule 164 Examined from Particles