Effective Energy Management of Hybrid AC–DC Microgrids With Storage Devices

Abstract

This paper proposes a stochastic framework for the optimal operation and management of hybrid ac–dc microgrids (MGs) in the presence of renewable energy sources (RESs) and storage devices. Hybrid ac–dc MGs can provide benefit over the traditional ac MGs by elimination of inverting equipment and reducing power losses caused by the ac–dc convertors. A stochastic load flow based on an unscented transform is employed to model the uncertainties of active and reactive loads, market power price, wind turbine, and photovoltaic output power. Additionally, a new powerful optimizer based on crow search algorithm (CSA) is devised to search the problem space. The proposed method uses a new two stage modification method to increase the search ability of CSA when avoiding premature convergence. The feasibility and performance assessment of the proposed framework are examined on an IEEE standard test system.