Improving Scheduling Performance of EV Charging using Binary Programming

Tirada Samsria and Ekachai Phaisangittisagulb

Department of Electrical Engineering, Faculty of Engineering, Kasetsart University

50 Phaholyothin Rd., Chatuchak, Bangkok 10900, Thailand

                                              Email:This email address is being protected from spambots. You need JavaScript enabled to view it. , This email address is being protected from spambots. You need JavaScript enabled to view it.           

Manuscript received September 28, 2015

Revised October 22, 2015

Abstract

Due to the global warming problem and the increment of the fossil fuel price, the Electric Vehicles (EVs) have been developed and implemented on the cutting edge of power distribution system. The EVs can be performed a different role of either generation or load consumption. However, if the charging management of EVs system is not effective, it may lead to an unreliable grid system, which is one of the major concerns in EVs applicability. The objective of this research is to propose an effective scheduling method for charging EVs. Our approach presents a new objective function that includes a waiting time to charge, earliest deadline, and time to fully charge into consideration that is able to efficiently allocate the limited energy and also improve the Peak-to-Average Ratio (PAR) by using binary integer programming as an optimization method. The database used in this study is based on National Household Travel Survey organization (NHTS 2009), which is widely used in implementation of EVs scheduling. In addition, IEEE 69 bus is also applied as a grid system in our experiments. The simulation results show that the proposed scheduling method is not only able to reduce the peak demand of the system but to help improving the PAR as well. The main advantage of the proposed method can improve the overall performance of the EVs charging system without necessarily reconfiguring the distribution system to support the emerging of the EVs. Hence, the proposed method can be applied to manage EVs scheduling with different power system configuration.

Keywords: Electric Vehicles, Charging Scheduling, Peak-to-Average Ratio, Binary Programming

pdf-iconpdf File  Size: 161.35 KB

 

mutengineer@gmail.com

Mahanakorn University of Technology

140 Moo 1, Cheum-Sampan Road, Nongchok, Bangkok, Thailand 10530

Tel: +(662)988-3655  Fax: +(662)988-4027

designed by sutit.ongart@gmail.com