Disfani, Vahid R.
Karrar, Abdelrahman A.; Ahmed, Raga; Barati, Masoud
College of Engineering and Computer Science
University of Tennessee at Chattanooga
Place of Publication
The global electric vehicle (EV) industry continues to expand rapidly. From the power grid perspective, expanding EV adoption could adversely impact the grid if its load is left uncontrolled. EV users also deal with challenges such as high charging time and low charger availability, especially in urban areas with huge populations and various types of charging demands. This dissertation initially reviews EV charging technologies and presents a new classification. Next, to address the EV charging management challenges, it investigates optimal EV charging management models and studies the coordination of different charging methods and technologies. This work has two major parts: (i) EVs' Operation and Control Algorithm and (ii) EVs' Optimization Considering Multiple Charging Technologies. In the first part of this dissertation, a distributed optimization framework is developed based on the alternating direction method of multipliers (ADMM) as an exchange problem to solve the electric vehicle charging management problem (EVCMP). Next, the proposed framework is expanded by employing a collaboration layer between different EV aggregators (EVA) to increase the optimization's overall efficiency while preserving EVAs' independence. The proposed coordinated distributed platform (CDP) enhances the load profile's smoothness compared to the locally coordinated and uncoordinated charging platforms and decreases EV charging costs. In the second part, we introduced a multi-charger framework including both fixed and mobile charging stations for optimal operation of EVs, which covers the shortcomings of stand-alone usage of each charging technology. The proposed framework selects the best charging station type and location to minimize the users' overall charging time and cost and mitigate the stress on the electricity network caused by EV charging, especially during peak hours.
This work's completion is largely due to the encouragement, guidance, and friendship of many people. I take this opportunity to express my recognition to the people who have been essential for its successful completion. First, I would like to show my greatest appreciation to my supervisor Dr. Vahid R. Disfani, for his invaluable advice, continuous support, and the freedom he gave me during my Ph.D. He taught me the methodology to carry out the research and present the research work as clearly as possible, and patiently listened to all my questions. Moreover, he created a friendly atmosphere at ConnectSmart group, and as he always believed, he made a family of us. Dr. Disfani, it was a great privilege and honor to work and study under your guidance. I am also very thankful to all my committee members: Dr. Abdelrahman A. Karrar, Dr. Raga Ahmed, and Dr. Masoud Barati, for making the time to read my work and providing me with excellent suggestions and comments. Dr. Karrar, you deeply have amazed me with your leadership skills and hard work and inspired me with your passion for the power system, not to mention that your door has always been open to students. Dr. Raga, thank you for always being positive, supportive, and attentive with each of your students. Dr. Barati, thank you for your willingness to serve on my committee and support my doctoral training. My sincere thank also goes to all my friends from ConnectSmart Lab: Pablo, Farog, Shailesh and, Jim. I feel very privileged to have worked with such intelligent people, each one of you has inspired me to pursue the best of myself. It is my privilege to thank my dear wife, Sofia, for putting up with an absentee husband during this process. Thank you for your constant encouragement and support throughout my research period. Last but not least, I am extremely grateful to my parents for their love, caring, and sacrifices for educating and preparing me for the future. Without you, non of this would be possible.
Ph. D.; A dissertation submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Doctor of Philosophy.
Battery charging stations (Electric vehicles); Electric vehicles--Batteries; Mathematical models
xiii, 145 leaves
Afshar, Shahab, "Optimal electric vehicle charging management: coordination of multiple charging methods and technologies" (2022). Masters Theses and Doctoral Dissertations.