PhD thesis defense to be held on November 8, 2022, at 14:00 (Conference hall B.0.10, ground floor, new ECE bulding)
Picture Credit: Theodoros Theodoropoulos
Thesis title: Application of convex optimization algorithms on Electric Vehicle charging demand side management
Abstract: The ever-increasing Electric Vehicle (EV) fleet will undoubtedly stress the power system that requires scalable solutions to ensure normal grid operation and seamless EV charging. Fairness of EV charging power allocation and alignment to voltage restrictions is also essential. Towards that end, this paper introduces an EV charging allocation framework that takes into account residential power needs, EV charging demand and distribution-line voltage constraints. Our approach breaks down the charging problem into two parts; firstly, it allocates power to distribution line buses according to the weighted proportional fairness criterion and takes into account their specific EV fleet demand. Secondly, as an outcome of a constrained least squares optimization process, each EVs charging power is assigned. Both problems are solved by centralized reference convex optimization algorithms as well as scalable distributed ones introduced to address the charging needs of large EV fleets and long infrastructures. Rigorous analysis proves that the solution of distributed algorithms is close to centralized reference ones. Daily EV charging simulation results indicate a more balanced EV charging power allocation when comparing proportional fairness to linear and quadratic power allocation approaches. At the same time, the problem of management in a wireless and dynamic (on-the-go) charging environment is being studied in order to harmonize the total charging power of a number of vehicles to a desired profile.
Supervisor: Professor Emeritus Nikolaos Uzunoglou
PhD Student: Theodoros Theodoropoulos