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Designing a Neuro-Fuzzy controller with CRPSO and RLSE algorithms to control voltage and frequency in an isolated microgrid

With increasing the distributed energy resources in the power system, voltage and frequency control in microdrigs becomes one of the major concerns for the system operators. In this paper, firstly, a type of improved droop control is proposed and secondly, in order to remove the dependency of droop to transmission line parameters in the complex microgrids, the authors have used the neuro-fuzzy controller with learning system based on the Craziness-based particle swarm optimization (CRPSO) and Recursive least square error (RLSE) methods which has enough convergence in neuro-fuzzy controllers. Following this, the results are compared with the conventional neuro-fuzzy controller (BP-LSE) and the simulations verify the effective performance of theproposed approach. Finally, the proposed controller is simulated with 1,3 and 11 buses test systems