Multi-objective optimization and energy management in renewable based AC/DC microgrid. (August 2018)

• Record Type: Journal Article
• Authors: V., Indragandhi; R., Logesh; V., Subramaniyaswamy; V., Vijayakumar; Siarry, Patrick; Uden, Lorna
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 179
• Page End: 198
• Publication Date: 2018-08
• Subjects: AC micro-grid -- DC micro-grid -- MOPSO -- Fuel cell -- Photovoltaic -- Wind; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.01.023
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: 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.