CLPSO based droop optimization technique for DC Microgrid

Droop control technique is the prominent primary control method to attain proportional load sharing and voltage regulation in a DC micro-grid. In this paper, an optimization technique is used to obtain the optimal droop parameters for the primary control mechanism, considering the required constraints and loading condition. Moreover, comprehensive learning particle swarm optimization technique (CLPSO) is adopted over the conventional particle swarm optimization technique (PSO) method to obtain the droop gains for the primary control mechanism of dc microgrid system. The cost function for the optimization problem is formulated by taking voltage regulation error and proportional load sharing into account. This cost function converges to global minima during iterative operation of the swarm optimization algorithm, resulting in the optimal droop and voltage parameters.