Frequency Control of Microgrid under Islanded Condition Using Fuzzy-PI based Controller

Abstract

With increasing power demand, the pressure on conventional sources of energy has increased leading to depletion of fossil fuels. Burning of fossil fuels is one major factor that contributes to pollution and global warming. All these issues related with conventional sources of energy has led to a new concept of power generation which employs the use of renewable energy resources (RESs). The use of RES’s lead to issue of power fluctuation in the system which further causes frequency deviations. The load frequency changes abnormally, which is fuzzy in nature, due to low system inertia and unpredictable variation in wind and solar irradiance level. The frequency fluctuation caused on account of integration of RESs is a well recognized phenomenon. To control these fluctuations storage units can be added in the system. Integration of storage units in the system also increases the reliability of the system by ensuring continuous supply of power. However, apart from integrating storage units in the system a proper control scheme can be developed for frequency control of the microgrid. In this work a fuzzy-PI based control scheme is proposed, which automatically updates the control parameters on occurrence of any disturbance in the system. A microgrid under islanded condition consisting of photovoltaic and wind generator units along with diesel generator set and storage units is considered. Further, performance of the proposed fuzzy-PI controller is verified with that of an autotuned PI controller, which is readily available in MATLAB/simulink library to get faster response. The steady state response is found minimum in case of autotuned PI controller as compared to fuzzy-PI controller.The proposed fuzzy-PI controller is validated based on ITAE (4-7%) which is higher than that attained from autotuned-PI controller. The control schemes are validated for single area hybrid microgrid and two area microgrid system. The developed model is simulated in MATLAB/Simulink environment.