2018/06/28 by M. Hadi Amini, Amini, M. Hadi, Javad Mohammadi +3
Engineering · #Distributed #Electric Vehicles and Infrastructure #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Parallel #Smart Grid Energy Management #Systems and Control (eess.SY) #Transportation and Mobility Innovations #and Cluster Computing (cs.DC) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1806.11190
openalex publication_date 2018/06/28 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
Plug-in Electric Vehicles (PEVs) play a pivotal role in transportation\nelectrification. The flexible nature of PEVs' charging demand can be utilized\nfor reducing charging cost as well as optimizing the operating cost of power\nand transportation networks. Utilizing charging flexibilities of geographically\nspread PEVs requires design and implementation of efficient optimization\nalgorithms. To this end, we propose a fully distributed algorithm to solve the\nPEVs' Cooperative Charging with Power constraints (PEV-CCP). Our solution\nconsiders the electric power limits that originate from physical\ncharacteristics of charging station, such as on-site transformer capacity\nlimit, and allows for containing charging burden of PEVs on the electric\ndistribution network. Our approach is also motivated by the increasing load\ndemand at the distribution level due to additional PEV charging demand. Our\nproposed approach distributes computation among agents (PEVs) to solve the\nPEV-CCP problem in a distributed fashion through an iterative interaction\nbetween neighboring agents. The structure of each agent's update functions\nensures an agreement on a price signal while enforcing individual PEV\nconstraints. In addition to converging towards the globally-optimum solution,\nour algorithm ensures the feasibility of each PEV's decision at each iteration.\nWe have tested performance of the proposed approach using a fleet of PEVs.\n