151. Optimal energy management scheme for electric vehicle integration in microgrid
- Author
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Venkateswaran Lakshminarayanan, Kaushik Rajashekara, Sumit Pramanick, Adel Gastli, and L. Ben-Brahim
- Subjects
Battery (electricity) ,050210 logistics & transportation ,Schedule ,business.product_category ,energy management ,Microgrid ,Computer science ,Energy management ,020209 energy ,05 social sciences ,Control engineering ,02 engineering and technology ,Power (physics) ,Charging station ,EV forecasting ,Control theory ,0502 economics and business ,Electric vehicle ,Multi-Agent System (MAS) ,0202 electrical engineering, electronic engineering, information engineering ,Electric vehicle (EV) ,business - Abstract
Electric vehicles (EV) connected to a charging station in a microgrid system is a potential power source for participation in energy management (EM). However, an autonomous controller scheme is required to schedule the charging and discharging of the EV battery for optimal EM. This paper proposes an intelligent EM controller for a workplace with EV integration. A Multi-Agent System (MAS) based coordinated optimization scheme is developed for EM. The optimal charging and discharging schedule is obtained by forecasting the trip pattern of EV based on regression by discretization methodology. Furthermore, the optimization scheme is designed considering monetary benefits to the workplace and the EV owner. The controller scheme is developed using Java Agent Development framework (JADE). The proposed EM scheme is tested with real-world data and the results are verified. 1 2017 IEEE. ACKNOWLEDGMENT This publication was made possible by NPRP grant # NPRP 8-627-2-260 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the author[s]. Scopus
- Published
- 2017