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1.智能电网教育部重点实验室(天津大学),天津市 300072
2.省部共建电工装备可靠性与智能化国家重点实验室(河北工业大学),天津市 300130
3.国网天津市电力公司电力科学研究院,天津市 300384
穆云飞(1984—),男,通信作者,博士,教授,主要研究方向:智能车网互动、综合能源系统能量管理。E-mail:yunfeimu@tju.edu.cn
金尚婷(1993—),女,博士研究生,主要研究方向:电力系统运行与优化、电动汽车与电网互动。E-mail:shangtingjin@tju.edu.cn
赵康宁(1994—),男,博士研究生,主要研究方向:电动汽车负荷预测、人工智能在电力系统中的应用。E-mail:zhaokn@tju.edu.cn
收稿:2023-10-23,
修回:2024-01-29,
网络出版:2024-02-23,
纸质出版:2024-04-10
移动端阅览
穆云飞,金尚婷,赵康宁等.“人-车-桩-路-网”深度耦合下的配电网协同规划与运行优化[J].电力系统自动化,2024,48(7):24-37.
MU Yunfei,JIN Shangting,ZHAO Kangning,et al.Collaborative Planning and Operation Optimization of Distribution Networks Under Deep Coupling of Drivers, Vehicles, Piles, Traffic and Networks[J].Automation of Electric Power Systems,2024,48(7):24-37.
穆云飞,金尚婷,赵康宁等.“人-车-桩-路-网”深度耦合下的配电网协同规划与运行优化[J].电力系统自动化,2024,48(7):24-37. DOI: 10.7500/AEPS20231023002.
MU Yunfei,JIN Shangting,ZHAO Kangning,et al.Collaborative Planning and Operation Optimization of Distribution Networks Under Deep Coupling of Drivers, Vehicles, Piles, Traffic and Networks[J].Automation of Electric Power Systems,2024,48(7):24-37. DOI: 10.7500/AEPS20231023002.
电动汽车(EV)作为连接交通电气化和电网清洁化的纽带和桥梁,可实现电力-交通-信息之间的深度耦合,形成电力-交通一体化的规划及运行架构。配电-交通融合系统(DTIS)中,EV充放电行为多时空动态交织、电能流-交通流-信息流深度融合、多利益主体动态博弈等大量不确定性因素使配电网的规划及运行优化的边界都将发生重大转变,但同时也给挖掘利用EV的移动储能特性和提升配电网灵活性带来了契机。为此,在分析“人-车-桩-路-网”深度耦合下配电网的形态演化特征基础上,剖析了新形态下配电网协同规划与运行优化所面临的新挑战,进而针对“人-车-桩-路-网”耦合下的EV灵活性建模、灵活域高效构建及预测、协同规划、运行优化4个方面关键技术展开讨论,并对相关技术问题的研究方向进行了展望。
Electric vehicles (EVs)
as a link and bridge connecting transportation electrification and grid cleanliness
can achieve deep coupling among electricity
transportation and information
forming an integrated planning and operation architecture of electricity and transportation. In the distribution-transportation integrated system (DTIS)
a large number of uncertain factors such as the multiple spatio-temporal dynamic interweaving of EV charging and discharging behaviors
deep integration of electricity flow
traffic flow and information flow
and dynamic game among multiple stakeholders will cause significant changes in the planning and operation optimization boundaries of the distribution network. However
at the same time
it also brings opportunities to explore and utilize the mobile energy storage characteristics of EVs and improve the flexibility of the distribution network. Therefore
based on the analysis of the morphological evolution characteristics of the distribution network under the deep coupling of drivers
vehicles
piles
traffic and networks
the new challenges faced by the collaborative planning and operation optimization of the distribution network in the new form are analyzed. Furthermore
four key technologies such as EV flexibility modeling
efficient construction and prediction of flexible regions
collaborative planning
and operation optimization under the coupling of drivers
vehicles
piles
traffic and networks are discussed
and the research directions of the related technical issues are prospected.
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