1 Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Department of Electrical Engineering, Technical University of Denmark4 Center for Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark5 Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark
A dual objective electric vehicle (EV) charging schedule optimisation is proposed here whereby both consumer driving requirements and grid constraints are respected. A day-ahead dynamic tariff (DT) for distribution systems is proposed as a price signal to EV fleet operators (FO) bidding into the day-ahead market. The DT acts to disperse charging at congested periods and locations, thereby preventing congestion on a day-ahead basis. The magnitude of the DT is determined from a simulated locational marginal prices (LMPs), and the time extent of the DT is determined from analysis of the system loading curve prior to the application of the DT. Case studies were performed using a sample distribution network modelled on a network from the Danish island of Bornholm. A variety of price profiles were used to illustrate the efficacy of this approach. The case study results show that this approach is highly efficient at grid congestion prevention, and the precise level of congestion that can be alleviated is dependent on the price profile of the optimisation period in question.
Ieee Power & Energy Society General Meeting, 2012
Day-ahead Dynamic Distribution System Tariff; Distribution System Constraints; Electric Vehicle (EV) Charging Schedule; Locational Marginal Pricing; Minimum EV Charging Cost
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2012 IEEE Power & Energy Society General Meeting, 2012