Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Open Access Dissertations and Theses Community
  3. Open Access Dissertations and Theses
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/27010
Title: Mitigation of Electric Vehicle Charging Effects on Distribution Grids Through Smart-Charging and On-board Solar Charging
Authors: MOBARAK, MUHAMMAD HOSNEE
Advisor: BAUMAN, JENNIFER
Department: Electrical and Computer Engineering
Keywords: Electric Vehicle;Smart Charging;Solar Energy;MPPT;GMPPT;Optimization;Solar-charged Electric Vehicle
Publication Date: 2021
Abstract: Electric vehicles (EV) have become very popular in recent years because they are a more sustainable, efficient, and environmentally friendly transportation option than traditional fossil-fuel vehicles. Increased EV charging can cause overheating, accelerated aging, and eventual early failure of the distribution transformers, as the distribution networks have not been established foreseeing a large number of EVs as loads. This thesis makes contributions in two main areas to help reduce the accelerated aging of distribution transformers as the number of EVs on the road continues to rise. Firstly, vehicle smart charging is investigated to spread out the EV charging loads and hence decrease transformer heating and aging. Most EV smart charging algorithms require the use of extensive and costly infrastructure, including sensors, communication networks, controllable chargers, and central smart agents. This thesis proposes a new vehicle-directed smart charging strategy, called Random-In-Window (RIW) which allows individual vehicles to spread out their charging without any costly additional infrastructure. Detailed simulation results prove the advantages of this proposed algorithm. Secondly, to further reduce EV charging loads on the grid, a large-scale solar-charged electric vehicle (SEV) is proposed. While RIW smart charging has only grid benefits, SEVs can contribute to grid benefit, driver benefit, and environmental benefit, as shown through detailed simulation results, making it a viable solution to transformer aging mitigation. To turn the SEV concept into reality, this research also proposes a fast maximum power point tracking algorithm for partially shaded conditions, and an algorithm which optimizes photovoltaic (PV) cell size and arrangement along with the power electronic converter design for on-board solar charging. Thus, the proposed solutions in this research can help reduce distribution transformer aging as EV penetrations continue to rise and increase the environmental benefits of EVs through optimized solar charging.
URI: http://hdl.handle.net/11375/27010
Appears in Collections:Open Access Dissertations and Theses

Files in This Item:
File Description SizeFormat 
MOBARAK_MUHAMMADHOSNEE_202109_PhD.pdf
Access is allowed from: 2022-09-21
9.5 MBAdobe PDFView/Open
Show full item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue