Multi-objective optimization and energy management in renewable based AC/DC microgrid

• Published in: Computers & electrical engineering Vol. 70; pp. 179 - 198
• Main Authors: V., Indragandhi, R., Logesh, V., Subramaniyaswamy, V., Vijayakumar, Siarry, Patrick, Uden, Lorna
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.08.2018; Elsevier BV; Elsevier
• Subjects: AC micro-grid; Batteries; Computer Science; DC micro-grid; Distributed generation; Electric power grids; Energy management; Energy storage; Energy utilization; Exchanging; Fuel cell; Fuel cells; Hybrid systems; MOPSO; Multiple objective analysis; Optimization; Particle swarm optimization; Photovoltaic; Photovoltaic cells; Power management; Renewable resources; State of charge; Wind; Wind power; DC micro-grid; MOPSO; Wind; AC micro-grid; Photovoltaic; Fuel cell
• ISSN: 0045-7906; 1879-0755
• DOI: 10.1016/j.compeleceng.2018.01.023

The problems with the design of hybrid micro-grids are system price and service quality. In this paper, we solve these problems by utilizing renewable resources optimally, maintaining State of Charge (SOC) in batteries. The proposed system also defines the lowest rate for power exchanged between the AC/DC micro-grids. Photovoltaic and wind energy are utilized as key resources in the system. Also, storage banks are coupled to both micro-grids and the fuel cell is the hold-up resource to maximize the consistency of the generation system. Supervisory controller ensures the maximum utilization of resources and by maintaining SOC to manage the exchange of power between micro-grids. This research focuses on power management in AC/DC micro-grid, and its optimization has been investigated by Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. The result shows that MOPSO yields positive performance and the proposed system is recommended as the best substitute to improve electric energy utilization in remote areas.