This paper presents a single Quadratic Unconstrained Binary Optimization (QUBO) model of the combined optimization of both active and reactive power dispatch of an Electric Vehicle Aggregator (EVA). Its methodology integrates a new tri-layered, nested optimization framework that streamlines the process of selecting an optimum timetable of the EVA, checking its feasibility with grid limits at the Distribution System Operator (DSO) tier, and then distributing the ultimate schedule to each EV. The resulting framework results in a multi-level, comprehensive evaluation of the system, which generates economically optimal results of both the EVA and the DSO.
Vansh Suri, Neelu Nagpal, Ravi Sharma.
Department of Electrical and Electronics Engineering, MAIT, Sector-22, Rohini, Delhi-110086
Abstract: This paper presents a single Quadratic Unconstrained Binary Optimization (QUBO) model of the combined optimization of both active and reactive power dispatch of an Electric Vehicle Aggregator (EVA). Its methodology integrates a new tri-layered, nested optimization framework that streamlines the process of selecting an optimum timetable of the EVA, checking its feasibility with grid limits at the Distribution System Operator (DSO) tier, and then distributing the ultimate schedule to each EV. The resulting framework results in a multi-level, comprehensive evaluation of the system, which generates (a) economically optimal results of both the EVA and the DSO, b) detailed active and reactive power schedules on the cluster level of the electric vehicles, and (c) in-depth verification of the grid stability in the form of the voltage profiles, power factor, and system losses. Comparative studies indicate that this technique is easily better than benchmark techniques, and results in the reduction of up to 70.5% in total system cost and 29% in active power losses. The findings prove that the suggested QUBO framework can be effectively used as a strong, economically beneficial, and scalable approach to the problem of the demand management of electric vehicles in modern power systems.
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