Research on electric vehicle charging scheduling algorithms based on a 'fractional knapsack'
by Zhenzhou Wang; Xinyuan Li; Pingping Yu; Ning Cao; Russell Higgs
International Journal of Embedded Systems (IJES), Vol. 14, No. 1, 2021

Abstract: The large-scale disorderly charging of electric vehicles creates challenges for the security of power systems, especially power distribution systems. To avoid peak power consumption during the day and improve the utilisation rate of the power grid at night, a charging scheduling algorithm for electric vehicles based on a 'fractional knapsack' is proposed. Considering the constraints of the user's charging demand and charging system capacity, a charging model based on a fractional knapsack is established to optimise the peak-valley load difference and reduce load fluctuation and charging cost, which is the objective function. To verify the effectiveness of the proposed algorithm, the Monte Carlo method is used to simulate the charging demand of electric vehicles, and the disorderly charging and orderly charging scheduling are simulated and compared under a time-sharing tariff mode. The results show that the proposed scheduling algorithm improves the peak-valley difference of the power grid, reduces fluctuation in the power grid load, and improves the utilisation rate of the power grid.

Online publication date: Tue, 22-Dec-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Embedded Systems (IJES):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com