Charging strategy for electric vehicles using solar energy

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

13 Scopus citations

Abstract

Public charging networks for Electrical Vehicles (EV) is on the rise, with more than 1.3 million EVs deployed worldwide [1]. Whether for economic benefits (higher price per KWh for a faster charging) or for the sole purpose of priority, it has become a point of interest to set a strategy on how to prioritize EVs charging from a single network, especially if the power source is limited as in the case of renewable energy. In this paper, a strategy will be proposed for charging networks based on category prioritization. Time-multiplexing the power supply using controllers is the key component of this network logic, which will enable the network to control which EV gets more time being supplied with power and this control structure will also overcome the state-of-charge bias. A scenario of a shaded office parking with solar panels as power source was used to test the strategy, simulation and experiment were carried out to validate the control logic, simulation and experimental testing was successful and results showed this time-multiplexing method can enable the EV charging station to give priority to certain EV to charge faster and prevent the SOC from being the main drive in case of limited power source.

Original languageEnglish
Title of host publication2017 Saudi Arabia Smart Grid Conference, SASG 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538618769
DOIs
StatePublished - 8 May 2018

Publication series

Name2017 Saudi Arabia Smart Grid Conference, SASG 2017

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Charing Strategy
  • Controllers
  • Electric Vehicles
  • Solar Energy
  • Time Multiplexing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

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