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Model-Based Quantification of Load Shift Potentials and Optimized charging of Electric Vehicles

Smart Grid and Renewable Energy 2013年第5期4卷 398-408页

作者： Tobias Hahn Martin Schonfelder Patrick Jochem Vincent Heuveline Wolf Fichtner Institute of Process Engineering in Life Sciences Karlsruhe Institute of Technology(KIT)KarlsruheGermany Chair of Energy Economics Karlsruhe Institute of Technology(KIT)KarlsruheGermany University of Heidelberg Interdisciplinary Center for Scientific ComputingHeidelbergGermany

Managing the charging process of a large number of electric vehicles to decrease the pressure on the local electricity grid is of high interest to the utilities. Using efficient mathematical optimization techniques, the charging behavior of electric vehicles shall be optimally controlled taking into account network, vehicle, and customer requirements. We developed an efficient algorithm for calculating load shift potentials defined as the range of all charging curves meeting the customer’s requirements and respecting all individual charging and discharging constraints over time. In addition, we formulated a mixed integer linear program (MIP) applying semi-continuous variables to find cost-optimal load curves for every vehicle participating in a load shift. This problem can be solved by e.g. branch-and-bound algorithms. Results of two scenarios of Germany in 2015 and 2030 based on mobility studies show that the load shifting potential of EV is significant and contribute to a necessary relaxation of the future grid. The maximum charging and discharging power and the average battery capacity are crucial to the overall load shift potential.

关键词： Electric Mobility Load Shifting charging management Optimization

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Impact Analysis of EV charging with Mixed Control Strategy

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Journal of Energy and Power Engineering 2015年第8期9卷 731-740页

作者： Di Wu Haibo Zeng Benoit Boulet Department of Electric and Computer Engineering McGill University Montreal QC H3A OG4 Canada Department of Electric and Computer Engineering Virginia Tech Blacksburg VA 24061 USA

EVs （electric vehicles） have been widely accepted as a promising solution for reducing oil consumption, air pollution and greenhouse gas emission. The number of EVs is growing very fast over the years. However, the high adoption of EVs will impose a burden on the power system, especially for neighborhood level network. In this paper, we propose a mixed control framework for EV charging scheduling to mitigate its impact on the power network. A metric for modeling customer＇s satisfaction is also proposed to compare the user satisfaction for different algorithms. The impacts of the proposed algorithms on EV charging cost, EV penetration and peak power reduction are evaluated with real data for a neighborhood level network. The simulation results demonstrate the effectiveness of the proposed algorithms.

关键词： Neighborhood level network electric vehicle penetration level mixed control charging management user satisfaction.

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