A Survey on Application of Artificial Intelligence Techniques in Microgrid Control

Concerns over the energy and environmental crisis are driving the strategic integration of distributed generators (DGs) in power systems, hastening the shift to sustainable energy. Microgrids (MGs) emerged as self-reliant, localized power solutions for DGs integration, enhancing grid performance and reliability by allowing grid-connected and islanded modes of operation. Moreover, the dc nature of many DGs and household devices, together with the progress in power electronics, have shifted research from conventional ac MGs towards dc and hybrid ac/dc MGs, which increase the complexity and the number of control scenarios. Therefore, the MG control environment require advanced data-driven algorithms to overcome the stochasticity and non-linear characteristics of MGs systems. In this context, artificial intelligence (AI) techniques demonstrate high potential for enhancing the control and operation in the dynamic MG environment. This paper reviews the most recent research effort regarding the application of AI-based technology in the hierarchical control structure for ac, dc and hybrid ac/dc MG architectures.