Enhancement of microgrid dynamic responses under fault conditions using artificial neural network for fast changes of photovoltaic radiation and FLC for wind turbine

摘要: Microgrid is a low voltage electrical network with distributed generations, energy storage devices and controllable loads. This paper utilizes artificial neural (ANN) to predict the optimum voltages in order extract maximum power increment efficiency of photovoltaic system. In this regard, are achieved by genetic algorithm (GA). Then these values used ANN method. The results ANN-GA compared other methods that verified proposed method high accuracy which can track point (MPP) under different insolation temperature circumstances also, meet load demand less fluctuation around MPP.; also it increase convergence speed achieve MPP. As well as, evaluation fuzzy logic controller (FLC) comparison PI pitch angle wind turbine (WT) carried out. control output turbine, implementing active as inputs FLC, has faster responses, smoother curves, oscillation than aforementioned lead improve dynamic responses WT. models developed applied Matlab/Simulink program.