基于电动汽车分群的“风-网-车”联合消纳调度策略

doi:10.11930/j.issn.1004-9649.202005103

中国电力 ›› 2021, Vol. 54 ›› Issue (4): 107-118.DOI: 10.11930/j.issn.1004-9649.202005103

• 区域综合能源系统规划与运行技术专栏 • 上一篇下一篇

基于电动汽车分群的“风-网-车”联合消纳调度策略

陈岩¹, 靳伟¹, 王文宾¹, 李会彬¹, 韩胜峰¹, 王一鸣³, 钟嘉庆²

1. 国网河北省电力有限公司邢台供电分公司, 河北邢台 054001;
2. 河北省电力电子节能与传动控制重点实验室（燕山大学）, 河北秦皇岛 066004;
3. 中国铁路北京局集团有限公司, 北京 100860

收稿日期:2020-05-13 修回日期:2020-09-24 发布日期:2021-04-23
作者简介:陈岩(1982-),男,硕士,高级工程师,从事电力系统规划与新能源技术研究,E-mail:510124325@qq.com;靳伟(1976-),男,硕士,高级工程师,从事新能源电力系统研究,E-mail:jingw@126.com;钟嘉庆(1976-),男,通信作者,硕士,高级工程师,从事新能源电力系统研究,E-mail:jqzhong@ysu.edu.cn
基金资助:
国家自然科学基金资助项目(51877186)；国网河北省电力有限公司科技项目(KJ2019-016)

Scheduling Strategy for “Wind-Network-Vehicle” Joint Accommodation Based on Electric Vehicle Clustering

CHEN Yan¹, JIN Wei¹, WANG Wenbin¹, LI Huibin¹, HAN Shengfeng¹, WANG Yiming³, ZHONG Jiaqing²

1. Xingtai Power Supply Company, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China;
2. Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province(Yan Shan University), Qinhuangdao 066004, China;
3. China Railway Beijing Bureau Group Co., Ltd., Beijing 100860, China

Received:2020-05-13 Revised:2020-09-24 Published:2021-04-23
Supported by:
This work is supported by National Natural Science Foundation of China (No.51877186) and Science and Technology Project of State Grid Hebei Electric Power Co., Ltd. (No.KJ2019-016)

摘要/Abstract

摘要： 为解决电动汽车的大规模实时优化调度问题，在建立电动汽车状态矩阵的基础上，提出电动汽车状态集群划分新方法。定义功率满意度及时间满意度，加权和为用户满意度，并以经济收益与满意度最大为目标，构造基于电动汽车分群的“风-网-车”实时联合消纳调度模型。针对并网运行的风电场出力与电动汽车负荷不确定性问题，研究可信性理论与模糊机会约束的融合，引入可信性测度指标，对模糊机会约束条件进行清晰化等价处理。最后，采用考虑外点罚函数法并带收缩因子的粒子群优化算法对调度模型进行优化求解，通过算例验证该模型及调度策略的优越性。

关键词: 电动汽车分群, “风-网-车”联合消纳调度模型, 可信性理论, 粒子群优化算法, 外点罚函数法

Abstract: In order to solve the large-scale real-time optimization scheduling problem of electric vehicles, a new method is proposed for dividing electric vehicles into several state clusters based on establishment of the electric vehicle state matrix. The power satisfaction and time satisfaction are defined in this paper, and their weighted sum is the user’s satisfaction. By taking the maximum economic benefit and satisfaction as the goal, a “wind-network-vehicle” real-time joint accommodation scheduling model is constructed based on the electric vehicle clustering. Aiming at the problem of grid-connected wind farm output and the uncertainty of electric vehicle loads, this paper studies the fusion of credibility theory and fuzzy opportunity constraints, introduces credibility measures, and makes clear and equivalent treatment of fuzzy opportunity constraints. Finally, a particle swarm optimization algorithm with a shrinkage factor considering the outlier penalty function method is used to optimize the scheduling model, and a case is used to verify the superiority of the model and its scheduling strategy.

Key words: electric vehicle clustering, “wind-network-vehicle” joint accommodation scheduling model, credibility theory, particle swarm joint accomodation algorithm, outlier penalty function method

陈岩, 靳伟, 王文宾, 李会彬, 韩胜峰, 王一鸣, 钟嘉庆. 基于电动汽车分群的“风-网-车”联合消纳调度策略[J]. 中国电力, 2021, 54(4): 107-118.

CHEN Yan, JIN Wei, WANG Wenbin, LI Huibin, HAN Shengfeng, WANG Yiming, ZHONG Jiaqing. Scheduling Strategy for “Wind-Network-Vehicle” Joint Accommodation Based on Electric Vehicle Clustering[J]. Electric Power, 2021, 54(4): 107-118.

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https://www.electricpower.com.cn/CN/Y2021/V54/I4/107

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基于电动汽车分群的“风-网-车”联合消纳调度策略

Scheduling Strategy for “Wind-Network-Vehicle” Joint Accommodation Based on Electric Vehicle Clustering

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基于电动汽车分群的“风-网-车”联合消纳调度策略

Scheduling Strategy for “Wind-Network-Vehicle” Joint Accommodation Based on Electric Vehicle Clustering

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