基于电价引导的电动汽车充电双层优化策略

doi:10.3969/j.issn.1000－7229.2018.01.006

摘要/Abstract

摘要： 摘要：该文建立了基于电价引导的电动汽车充电双层优化模型。在上层模型中，通过优化代理商在各个时段的充电调度计划，使系统总负荷的方差最小。在下层模型中，代理商通过制定充电电价，引导电动汽车用户调整充电计划，以便使下层电动汽车响应负荷与上层调度计划一致。利用遗传算法对模型进行迭代求解，结果表明：与无序充电相比，对电动汽车充电负荷进行优化后，系统总负荷的方差明显减小，平抑了系统运行的波动性，建立的优化模型可以较好地实现上层系统的调度和下层电动汽车用户的自主响应。

关键词: 电动汽车, 电价引导, 需求响应, 双层优化

Abstract: ABSTRACT： This paper establishes a bi-level optimization model for electric vehicle charging based on electricity price guide. In the upper model, the variance of the total load of the power system is minimized by optimizing the dispatching plan of the aggregator in each period. In the lower model, the aggregator guides the users to adjust the charging plan by setting the charging price, to coincide with the upper dispatching plan. We use genetic algorithm to solve the model iteratively. The results show that, compared with disordered charging, the variance of the total load of the system decreases obviously and the fluctuation of the system is reduced after the optimization of the charging load of electric vehicle. It is proved that the proposed optimization model can achieve the dispatching of the system in upper layer and the autonomous response of electric vehicle in lower layer.

Key words: , HU Dequan, GUO Chunlin, YU Qinbo, YANG Xiaoyan

中图分类号:

TM 711

胡德权，郭春林，俞秦博，杨晓言. 基于电价引导的电动汽车充电双层优化策略[J]. 电力建设, 2018, 39(1): 48-.

HU Dequan, GUO Chunlin, YU Qinbo, YANG Xiaoyan. Bi-Level Optimization Strategy of Electric Vehicle Charging Based on Electricity Price Guide[J]. Electric Power Construction, 2018, 39(1): 48-.

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