Abstract:
This paper addresses the method of forecasting the wind and solar power and its application to an islanded microgrid (MG) model for load frequency control. Due to high penetration of renewable energy sources, the islanded MG suffers from lower equivalent inertia. The islanded MG faces several challenges in order to ensure the stable operation by maintaining the frequency and voltage at nominal value. The supply and demand power mismatch is mainly due to continuously changing solar irradiance, fluctuating wind speed, variable inertia, and load fluctuations. The intermittent nature of RESs can significantly affect the system stability; hence, the challenge lies in accurate forecasting of power from the renewable energy sources (RESs) so that a proactive arrangement is made available for compensation of active power or frequency variations. The forecasting will determine the correct estimate of power availability so that the power reserves can be activated prior to large variations in active power affecting the stability of the MGs. To address these challenges, a stochastic model of wind and solar has been developed using “Time series modeling” of the data obtained from Charanka Solar Park under Gujarat Energy Development Agency, India. Wind and solar power availability are forecasted using autoregressive integrated moving average (ARIMA) method including the seasonality factor. The proportional and integral (PI) controller is used for regulating the frequency fluctuations caused due to intermittency in the output of RESs and load power. Various load patterns are applied to the MG model to analyze its load frequency behavior along with variations in secondary sources.