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Summary 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.

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Summary This article proposes forecast‐based modeling and robust frequency control strategy in isolated microgrids (MGs) to improve its stability. The intermittency and variability in renewable generation is problem for its smooth integration to MGs considering frequency stability. Continuous rise in penetration levels of renewable energy sources (RESs) is the main motivation behind forecast‐based modeling and controller design for MGs. The disturbances that affect the frequency in the MG may come from the load side and/or the generation sides. In MGs, at the generation side, the forecast of power from RESs is usually obtained to get a rough estimate of available renewable power. The forecasted power always differs from the actual one, so the secondary frequency controller may get overburdened due to forecast error resulting in abnormal frequency deviation that may lead to unstable power system. The proposed H∞ based robust control design considers the forecast error which improves the system stability and performance against disturbances coming from load/generation side. First, a long short term memory based recurrent neural network has been used to forecast the renewable power availability. Thereafter a H∞ controller is designed, and it is shown through extensive simulation studies that the H∞ controller outperforms optimized PID controllers so far as rejecting the effects of uncertainties in RESs, forecasting errors, and model parameter variations are concerned. The proposed robust controller design is also validated with real time simulator (OP4510) made by Opal‐RT. The controller hardware in the loop (CHIL) test has been done taking the simulation time step of 50 μS.

In this work, the contribution of wind turbine generator (WTG) to support micro-grid (MG) during depressed frequency condition has been studied with a modified strategy for improving the primary load frequency response of MG. The majority of existing deloading techniques to estimate the reference power are based on the linear relationship. Hence they are not so accurate to mimic the actual speed versus power dynamics of turbine rotor during deloading operation which is inherently nonlinear in nature. In this work, the existing methods have been analyzed in detail with an aim to improve the performance. Based on the analysis a modified deloading method assuming non-linear relation between rotor speed and power of WTG system has been proposed which shows the improved load frequency response in MG. The proposed deloading technique is simulated and validated using real-time digital simulator (OP4510) for the variation in load and generation inside an islanded MG. The results obtained using modified deloading method are compared with existing deloading method and it is found that proposed deloading method handles the non-linearity of the system during deloading operation and also it contributes more power to MG in response to load demand at the cost of slight increase in the speed of turbine rotor.