Optimal Power Control in Distributed Generation Units in an Islanded Microgrid

Abstract

This article studies the effect of new optimization techniques with the aim of finding the best solution using a fuzzy approach for operating an independent microgrid. The power flow technique is used to model and solve the problem of optimal active and reactive power control of distributed generation units (DGs) in an island microgrid (MG), while taking into account the improvement of the voltage profile and the voltage stability index by regulating the droop characteristics of DG sources. The suggested algorithms, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search (HS), Hybrid HS-GA, and Teaching-Learning Based Optimization, solve the optimization issue (TLBO). The numerical results of optimization algorithms are compared in terms of best solution, number of iterations, and convergence rate. Regarding multi-objective nature of the problem, the non-dominated sorting method is used to obtain the Pareto front for all algorithms. Finally, the best solution is selected from Pareto solutions using proposed fuzzy approach. Simulation results on the standard IEEE 33-bus network in MATLAB show that the TLBO algorithm has higher efficiency, and faster convergence rate compared to other methods in this study.