Switching signal reduction of load aggregator with optimal dispatch of electric vehicle performing V2G regulation service

M. Shafiul Alam, Md Shafiullah, Juel Md Rana, M. S. Javaid, Usama Bin Irshad, Muhammad Athar Uddin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Environmental concerns over the production of greenhouse gas have led to the development of environmental friendly transportation such as electric vehicle (EV). As the number of EVs is increasing day by day, it will have a great impact on grid operation and electricity market. Significant amount of EV charging during peak hour will cause branch congestions and low voltage. Moreover, high penetration of EVs plays an important role in altering electricity price. Thus, optimal scheduling of EVs charging is inevitable from the perspective of both system reliability and market. Load aggregators can combine the capacities of many EVs to participate in wholesale energy market. In this paper, optimal dispatch algorithm of EVs is developed and tested on a system consisting 1000 EVs. The advantage of the algorithm is that it requires less number of communication signals and less expensive infrastructure. EVs are turned on and turned off in binary fashion based on priority to follow the regulation signal.

Original languageEnglish
Title of host publication2016 International Conference on Innovations in Science, Engineering and Technology, ICISET 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509061228
DOIs
StatePublished - 14 Feb 2017

Publication series

Name2016 International Conference on Innovations in Science, Engineering and Technology, ICISET 2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Dispatch algorithm
  • Electric vehicle
  • Greenhouse gas
  • Load aggregator
  • Regulation down
  • Regulation up
  • Switching signal

ASJC Scopus subject areas

  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computer Science Applications

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