Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published December 2014 | public
Journal Article

Electric Vehicle Charging in Smart Grid: Optimality and Valley-filling Algorithms

Abstract

Electric vehicles (EVs) offer an attractive long-term solution to reduce the dependence on fossil fuel and greenhouse gas emission. At the same time, charging a large fleet of EVs distributed across the residential area poses a challenge for the distribution network. In this paper, we formulate this problem by building on the optimal power flow (OPF) framework to model the network constraints that arises from charging EVs at different locations. To overcome the computational challenge when the control horizon is long, we study a nested optimization approach to decompose the joint OPF and EV charging problem. We characterize the optimal EV charging schedule to be a valley-filling profile, which allows us to develop an efficient offline algorithm with significantly lower computational complexity compared to centralized interior point solvers. Furthermore, we propose a decentralized online algorithm that dynamically tracks the valley-filling profile. Our algorithms are evaluated on the IEEE 14 bus system with real residential load profiles, and the simulations show that our online algorithm performs almost optimally under different settings.

Additional Information

© 2014 IEEE. Manuscript received September 30, 2013; revised March 11, 2014; accepted June 11, 2014. Date of publication July 01, 2014; date of current version November 18, 2014. This work was supported in part by grants from the Research Grants Council of Hong Kong Project No. RGC CityU 122013 and SRG ISTD 2012037. The guest editor coordinating the review of this manuscript and approving it for publication was Prof. Yih-Fang Huang. The authors gratefully acknowledge helpful discussions with Steven H. Low at Caltech.

Additional details

Created:
August 22, 2023
Modified:
October 26, 2023