Frequency and Active Power Control of Interconnected Microgrids: An ANN-Based PI Tuning Approach

Frequency and tie-line power control of interconnected microgrids (IMGs) are a significant challenges due to the non-linear behavior of their structures. The nonlinearity and complexity of IMGs make it challenging to achieve desirable performance using classical and inflexible control structures across a wide range of operating conditions. As a result, an intelligent control systems is a promised solution to address this issue. In this study, an artificial neural network (ANN) is employed for the online tuning of the coefficients of proportional-integral (PI) controllers, which are the most widely used control structure in practice. The proposed control strategy has been implemented on two AC-IMGs using a simplified frequency response model. The simulation results highlight that the ANN-enhanced PI controller exhibits superior performance compared to the traditional PI controllers across a variety of operating conditions.