Fuzzy PI controller-based model reference adaptive control for voltage control of two connected microgrids

An efficient control strategy for two connected microgrids (MGs) is proposed to ensure stable and economic operation. One of the most important means of improving energy efficiency is to achieve the best response for sudden and stochastic disturbances to which the MGs are subjected. Traditionally, MGs are controlled using a linear controller, such as conventional proportional-integral (PI) controller. Fuzzy PI (FPI) controller-based model reference adaptive control that can adapt to a wide range of operating conditions for regulating the voltage is investigated and its performance is compared with the conventional linear PI controller that is not able to mitigate these disturbances efficiently. Parameters of the proposed controller are optimised using an advanced optimisation technique called global porcellio scaber algorithm (GPSA). Performance of the controllers is demonstrated on two connected microgrids for a number of scenarios such as load variations, weather fluctuations and faults. Simulation results verify that the proposed control strategy is effective and feasible under various operating conditions for this system. The results also show that the dynamic performance of the system with the model reference adaptive fuzzy PI (MRAFPI) controller is better than that with the most common controller used for this application, the conventional PI controller, for different operating conditions.