Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

Hui Cai, Wenjuan Du, Timothy Littler, Haifeng Wang, S. Gao, X. P. Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.
Original languageEnglish
Title of host publicationProceeding of the 2nd IET International Conference in Renewable Power Generation (RPG2013)
Volume2013
Edition623 CP
Publication statusPublished - Sep 2013

Keywords

  • Micro-grid; day-ahead schedule; charging/discharging strategy; electric vehicle (EV); serial quadratic programming (SQP)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Cai, H., Du, W., Littler, T., Wang, H., Gao, S., & Yu, X. P. (2013). Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids. In Proceeding of the 2nd IET International Conference in Renewable Power Generation (RPG2013) (623 CP ed., Vol. 2013)