Supervisory Energy Management in Hybrid AC-DC Microgrids Based on a Hybrid Distributed Algorithm

Abstract

As awareness of human global footprint grows, solution is investigated to reduce greenhouse gas emission (GHG). To reduce the carbon intensity of electricity production, a large deployment of renewable energy sources (RESs), such as solar panels and wind turbine, has become a mandatory goal. Therefore, more and more microgrids (MGs) appear. In this context, this paper proposes an effective framework for optimal operation management of hybrid AC-DC microgrids (MGs) incorporating both dispatchable and non-dispatchable energy sources as well as battery energy storage system (BESS). The proposed method is constructed based on mixture of an alternating direction method of multipliers (ADMM) and firefly algorithm (FA) as a non-linear optimization algorithm. The performance of the ADMM-MFA is assessed using a typical hybrid AC-DC microgrid. The simulation results show the high efficacy and accuracy of the proposed method in comparison with other well-known methods.