Optimization of Droop Control Coefficients in a Isolated Microgrid Cluster Using Particle Swarm Optimization

Abstract

The isolated operation of microgrid clusters (MGC) must ensure proper voltage and frequency control continuously, in addition to maintaining the load and establishing an efficient distribution among the microgrids (MGs). The droop control technique is the most adopted method to perform the primary control of MGs. Therefore, the optimization of the droop control coefficients is one issue that need to be addressed to achieve the optimal MGC operation. This article presents a new objective cost function aimed at minimizing the system's total operating cost while ensuring effective voltage and frequency control within the established threshold values. The particle swarm optimization (PSO) metaheuristic optimization algorithm is used to solve the optimization problem and obtain the optimal values of the droop control coefficients that guarantee MGC stability and loss minimization. An isolated MGC is implemented in the Matlab/Simulink environment. Each MG consists of a gridsupporting inverter, an inductive-capacitive filter, a power transformer, and transmission lines connecting each MG. The results obtained in different scenarios ensure effective frequency and voltage control, as well as loss minimization by applying the optimal droop coefficients obtained through PSO.