
The control and energy management problems of microgrids (MGs) are challenging due to the high level of uncertainties and disturbances such as changes in demands, mechanical powers, and solar energies. So, intelligent computing is needed to be developed for these systems. This paper uses an optimal and robust fuzzy controller for automatic voltage and frequency regulation. The fuzzy logic develops the resistance against uncertainties and disturbances such as irradiation, wind power changes, and load demand variation. The introduced controller uses appropriate and effective criteria that include rising time, settling time, overshoot, and the degree of resistance of the control system to uncertainties and perturbation effects. Through simulations and compassion with conventional regulators, the better accuracy of the suggested approach is demonstrated.
Settling time, Intelligent control, Smart Grid Applications, Artificial intelligence, Control (management), Quantum mechanics, Electric power system, Engineering, Microgrid Control, Step response, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), Demand Response in Smart Grids, Electrical and Electronic Engineering, Biology, Load Frequency Control, Control engineering, Physics, Load Frequency Control in Power Systems, Controller (irrigation), Power (physics), Computer science, Agronomy, Intelligent Control, Fuzzy logic, Load Control, Fuzzy control system, Control and Systems Engineering, Electrical engineering, Physical Sciences, Telecommunications, Control and Synchronization in Microgrid Systems, Overshoot (microwave communication), Wind power, Mathematics
Settling time, Intelligent control, Smart Grid Applications, Artificial intelligence, Control (management), Quantum mechanics, Electric power system, Engineering, Microgrid Control, Step response, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), Demand Response in Smart Grids, Electrical and Electronic Engineering, Biology, Load Frequency Control, Control engineering, Physics, Load Frequency Control in Power Systems, Controller (irrigation), Power (physics), Computer science, Agronomy, Intelligent Control, Fuzzy logic, Load Control, Fuzzy control system, Control and Systems Engineering, Electrical engineering, Physical Sciences, Telecommunications, Control and Synchronization in Microgrid Systems, Overshoot (microwave communication), Wind power, Mathematics
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