宫鑫, 苏禹, 张小凤, 黄相杰. 计及激励型需求响应的电动汽车聚合商充电优化调度[J]. 现代电力, 2019, 36(6): 16-22.
引用本文: 宫鑫, 苏禹, 张小凤, 黄相杰. 计及激励型需求响应的电动汽车聚合商充电优化调度[J]. 现代电力, 2019, 36(6): 16-22.
GONG Xin, SU Yu, ZHANG Xiaofeng, HUANG Xiangjie. Optimal Charging Scheduling for Electric Vehicle Aggregator Considering Incentive Demand Response[J]. Modern Electric Power, 2019, 36(6): 16-22.
Citation: GONG Xin, SU Yu, ZHANG Xiaofeng, HUANG Xiangjie. Optimal Charging Scheduling for Electric Vehicle Aggregator Considering Incentive Demand Response[J]. Modern Electric Power, 2019, 36(6): 16-22.

计及激励型需求响应的电动汽车聚合商充电优化调度

Optimal Charging Scheduling for Electric Vehicle Aggregator Considering Incentive Demand Response

  • 摘要: 研究了电动汽车聚合商如何决策最优的经济激励值和充电量,以达到收益最大化的目的。提出了用户向聚合商交流其充电情况的主动需求响应方式;构造了基于经济激励的电动汽车聚合商的最优充电调度模型,所建立的调度模型是一个二层模型,上层以聚合商收益最大为目标,以用户主动需求响应量为约束,下层为实时电力市场的出清模型,上层模型中的市场电价来自于下层模型;将该模型转化为混合整数线性规划模型,采用拉格朗日替代法与分支切割法的协同组合方法求解。算例分析表明所提模型能够提高聚合商的收益。

     

    Abstract: An active demand response approach was proposed for electric vehicle users by reporting their charging status to the aggregator. Optimal charging scheduling model of the aggregator in the real-time electricity market considering coupon-based active demand response was built. This bi-level model was constructed with the upper level model aiming at maximizing the aggregator’s revenue constrained the consumer’s active demand response, and the lower level market clearing model providing market price for the upper model. The optimal charging scheduling model is a mixed integer linear programming model solved by the combination of Surrogate Lagrangian Relaxation and Branch-And-Cut method. The example analysis shows that the proposed model can increase the aggregator’s profit.

     

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