A Bi-Level Programming Approach for Optimal Design of EV Charging Station

B. Zeng, Houqi Dong, Xuan Wei, Fuqiang Xu, R. Sioshansi, Min Zhang
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引用次数: 1

Abstract

This paper proposes a methodology to decide optimal design of grid-connected electric vehicle (EV) charging systems with renewable energy resources (RCS) in the future smart-grid. Distinct from existing studies, the proposed planning model is intended for a fully liberalized market environment and the potential strategic nature of EV users in their charging actions are explicitly considered. To formulate such problem, a bi-level programming framework with equilibrium constraints has been introduced. In this formulation, the optimal configuration plan of RCS and its operation/pricing schemes are determined simultaneously to maximize the total profits of RCS owner, while accounting for the interaction of EV users during the planning horizon; moreover, the potential uncertainties associated with RCS due to the volatility of market prices, renewable availability, and traffic flows are also considered in our planning problem, by using robust optimization approach. The bi-level robust optimization model is transformed into an equivalent single-level linear program, by replacing the lower-level problem with KKT conditions to solve. The simulation results from case studies demonstrate the effectiveness of the proposed approach.
电动汽车充电站优化设计的双层规划方法
提出了一种未来智能电网中可再生能源并网电动汽车充电系统优化设计的决策方法。与现有研究不同的是,所提出的规划模型旨在实现完全自由化的市场环境,并明确考虑了电动汽车用户充电行为的潜在战略性质。为了表述这类问题,引入了具有平衡约束的双层规划框架。在此公式中,考虑电动汽车用户在规划区间内的交互作用,同时确定RCS的最优配置方案及其运营/定价方案,使RCS所有者的总利润最大化;此外,由于市场价格、可再生能源可用性和交通流量的波动,与RCS相关的潜在不确定性也被考虑在我们的规划问题中,通过使用鲁棒优化方法。将双层鲁棒优化模型转化为等效的单层线性规划,用KKT条件代替下层问题求解。实例仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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