Coordinated Control of Aichi Microgrid for Efficient Power Management Using Novel Set Point Weighting Iterative Learning Controller

Abstract

A novel Set Point Weighting Iterative Learning Controller (SPW-ILC) has been proposed for voltage stabilization at AC/DC bus, coordinated control among the distributed sources in the modeled hybrid microgrid (HMG) and synchronization of HMG with utility grid. The Aichi Micro grid test system located at Aichi Institute of Technology, Japan has been considered for the simulation studies and modeled in MATLAB/Simulink environment. The Aichi microgrid can be operated in autonomous mode as AC system and DC system. When it is working as DC system, the dc bus voltage is maintained stable by incorporating dedicated fuzzy logic controllers (FLC) for DC-DC converters due to the variable distributed sources. Meanwhile, the bidirectional converter also called as Interlinking Converter (IC) located between ac bus and dc bus controlled by proposed SPW-ILC converts the DC voltage into AC voltage and meets AC loads. In AC system of autonomous mode, the inverters are controlled by proposed controller to meet the ac demands. The grid connected mode of Aichi microgrid system is performed by properly controlling the IC to meet ac and dc loads. The proposed SPW-ILC reduces the voltage deviation and maintains the power balance under variable source and load conditions. The results have been compared with the conventional proportional integral (PI) controller and FLC to validate the performance of the controller. The results show that the proposed SPW-ILC has efficiently control the voltage and maintain the power balance.