Improved Energy Management System for Wind Power-Based Microgrid with EV Charge Station

Abstract

This study aims to peak power shaving and reduce the cost of energy by using improved energy management system (EMS) in a microgrid. This study has three scenarios. In the first scenario, the EV charging station and the wind turbine operate standalone. In the second scenario, a microgrid structure including an energy storage system (ESS) and an EMS is established. The threshold algorithm has been used for the energy management. In the last scenario, fuzzy logic-based EMS is used for energy management. The impact of EV charge station and wind turbine on the grid and the cost of energy are analyzed for three scenarios. The results show that the use of microgrid-connected ESS significantly reduces the cost of energy and creates a more balanced load for the grid side. It is also proved that the EMS affects the energy losses. It is revealed that when the proposed fuzzy logic-based EMS is used, the energy cost is reduced by 78% and the peak power is reduced by 70%. Thus, it is seen that the proposed EMS successfully reduces both the cost of energy and the negative impact of EVs on the grid by balancing grid side load.

Keywords:

• energy management system
• wind power
• microgrid
• EV charge station
• threshold algorithm
• fuzzy logic

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Erdal Bekiroglu

Erdal Bekiroğlu received his B.Sc., M.Sc., and Ph.D. degrees from the Gazi University in the field of Electrical Technologies. He worked as a research assistant at Gazi University between 1996 and 2003. He is currently professor at the Department of Electrical and Electronics Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University. His research interests are drive and control of electrical machines, ultrasonic motors, intelligent control, and renewable energy systems.

Sadullah Esmer

Sadullah Esmer received his B.Sc. degree from the Ondokuz Mayis University in Electrical and Electronics Engineering, in 2018. He received his M.Sc. degree from Bolu Abant Izzet Baysal University in Electrical and Electronics Engineering, in 2023. He is currently research assistant at the Department of Electrical and Electronics Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University. His research interests are optimization algorithms, design of electrical machines, and smart grid technologies.