Intelligent charging control of power aggregator for electric vehicles using optimal control

• Main Authors: Alkawaz, Ali Najem, Kanesan, Jeevan, Mohd Khairuddin, Anis Salwa, Chow, Chee Onn, Singh, Mandeep
• Format: Article
• Published: Univ Suceava, Fac Electrical Engineering 2021
• Subjects: QA75 Electronic computers. Computer science; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/27966/

Vehicles (EVs) have been shown to be better for the environment since they emit lesser air pollutants compared to fuel-based vehicles. High penetration of EVs in the distribution network contributes to the increment of capital investment in smart grid technologies. This is because EVs' charging operation involves a considerably high level of electricity due to the size of EVs' battery charging period. Poor scheduling of EVs charging operation will lead to an increment in electricity consumption. This will then lead to overloading of distribution network, voltage quality degradation, power loss increment, and dispatch of uneconomical energy sources. Hence, coordinated, and smart charging schemes are vital in order to reduce charging costs. This paper proposes an optimized EV battery charging and discharging scheduling model using an ordinary differential equation (ODE) based on three charging scenarios. The daily charging and discharging schedule of EVs are optimized using optimal control. The result shows that the proposed optimized charging and discharging scheduling model reduces the charging cost up to approximately 50%.