Artificial Intelligence Driven Smart Hierarchical Control for Micro Grids—A Comprehensive Review

The increasing demand for energy combined with depleting conventional energy sources has led to the evolution of distributed generation using renewable energy sources. Integrating these distributed generations with the existing grid is a complicated task, as it risks the stability and synchronisation of the system. Microgrids (MG) have evolved as a concrete solution for integrating these DGs into the existing system with the ability to operate in either grid-connected or islanded modes, thereby improving reliability and increasing grid functionality. However, owing to the intermittent nature of renewable energy sources, managing the energy balance and its coordination with the grid is a strenuous task. The hierarchical control structure paves the way for managing the dynamic performance of MGs, including economic aspects. However, this structure lacks the ability to provide effective solutions because of the increased complexity and system dynamics. The incorporation of artificial intelligence techniques for the control of MG has been gaining attention for the past decade to enhance its functionality and operation. Therefore, this paper presents a critical review of various artificial intelligence (AI) techniques that have been implemented for the hierarchical control of MGs and their significance, along with the basic control strategy.