考虑EV用户响应特性的激励型DR的削峰效果和各方需求分析
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作者单位:

1.广东电网有限责任公司广州供电局;2.广州市奔流电力科技有限公司

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TM863???

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广东电网有限责任公司广州供电局科技项目(GZHKJXM20180072)


Analysis on Peak Shaving Effect and Needs of All Parties Based on Incentive Demand Response Considering Response Characteristics of EV Users
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1.Guangzhou Power Supply Bureau Co., Ltd,;2.Guangzhou Power Electrical Engineering Technology Co., Ltd.

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    摘要:

    为解决接入充电负荷的配电网峰荷增大带来的电网安全性问题,建立了考虑电动汽车(electric vehicle, EV)用户响应特性的激励型需求响应(demand response, DR)。首先,提出了考虑削峰效果和用户响应程度的激励机制。其次,分析了签约用户的响应特性,提出用户签约响应次数限值评估模型,建立考虑过响应和欠响应的用户响应模型。然后,建立了“网-商-车”参与DR的成本和效益模型,并提出基准补偿电价优化方法。最后,通过仿真研究了用户充电行为、基准补偿电价和充电功率对负荷响应情况的影响。该研究可为聚合商筛选签约用户、差异化设置签约要求和调节补偿电价提供参考。

    Abstract:

    In order to solve the security problem caused by the increase of peak load of the distribution network with charging load, an incentive demand response (DR) that considers the response characteristics of electric vehicle (EV) users is established. Firstly, the incentive mechanism considering the effect of peak load reduction and the response degree of users is proposed. Secondly, the response characteristics of contracted users are analyzed. The evaluation model of user's contract response times limit is proposed. And the model of user response considering over response and under response is established. Then, the cost and benefit model of grid company, aggregators and EV users participating in DR is established, and an optimization method of benchmark compensation price is proposed. Finally, the impact of the charging behaviors of contracted users, the benchmark compensation price and charging power on load response is studied by simulations. The research can provide a reference for aggregators to screen contracted users, set different contract requirements, and adjust compensation electricity prices.

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历史
  • 收稿日期:2021-02-20
  • 最后修改日期:2021-05-06
  • 录用日期:2021-07-26
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