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现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林省吉林市 132012
姜涛(1983—),男,博士,教授,博士生导师,主要研究方向:电力系统安全性与稳定性、可再生能源联网运行、综合能源系统。E-mail:tjiang@neepu.edu.cn
吴成昊(1996—),男,博士研究生,主要研究方向:电力系统灵活性、电力市场。E-mail:1202100019@neepu.edu.cn
李雪(1986—),女,通信作者,博士,教授,博士生导师,主要研究方向:电力系统安全性与稳定性、电力系统高性能计算、电力市场。E-mail:xli@neepu.edu.cn
收稿:2024-07-18,
修回:2024-10-22,
网络出版:2025-01-13,
纸质出版:2025-05-25
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姜涛,吴成昊,李雪等.计及V2G主动支撑的输配协同日前-实时优化调度[J].电力系统自动化,2025,49(10):87-100.
JIANG Tao,WU Chenghao,LI Xue,et al.Transmission and Distribution Coordinated Day-ahead and Real-time Optimal Scheduling Considering Active Support of Vehicle-to-Grid[J].Automation of Electric Power Systems,2025,49(10):87-100.
姜涛,吴成昊,李雪等.计及V2G主动支撑的输配协同日前-实时优化调度[J].电力系统自动化,2025,49(10):87-100. DOI: 10.7500/AEPS20240718006.
JIANG Tao,WU Chenghao,LI Xue,et al.Transmission and Distribution Coordinated Day-ahead and Real-time Optimal Scheduling Considering Active Support of Vehicle-to-Grid[J].Automation of Electric Power Systems,2025,49(10):87-100. DOI: 10.7500/AEPS20240718006.
新能源发电与电动汽车的广泛应用使电力系统运行更加复杂,输电网面临功率平衡挑战,亟须挖掘各类资源的有功、无功支撑潜力。考虑到主动配电网对电动汽车等分布式资源的聚合作用,提出了一种计及车网互动(V2G)主动支撑的输配协同日前-实时优化调度方法。首先,考虑能量市场、灵活性市场和无功辅助服务市场机制,构建市场环境下电动汽车V2G响应模型,分析电动汽车有功、无功支撑潜力;然后,计及不同利益主体的信息隐私,构建输配协同日前-实时分布式优化调度模型,通过协调各类有功、无功调节资源来满足系统功率供需平衡要求;最后,在测试系统中对所提优化调度方法进行分析验证。结果表明,所提方法可实现分布式可调控资源的优化调度,提高系统运行经济性和灵活性。
The widespread application of renewable energy generation and electric vehicles (EVs) has made the operation of the power systems more complex
which poses a power balance challenge to the transmission network. It is urgent to tap into the potential for active and reactive power support of various resources. Considering the aggregation of active distribution networks on distributed resources such as EVs
this paper proposes a transmission and distribution coordinated day-ahead and real-time optimal scheduling method considering the active support of vehicle-to-grid (V2G). First
considering the mechanisms of energy market
flexibility market
and reactive power ancillary service market
a V2G response model for EVs under market environment is constructed to analyze the active and reactive power support potential of EVs. Then
considering the information privacy of different stakeholders
a transmission-distribution coordinated day-ahead and real-time distributed optimal scheduling model is constructed
which coordinates various active and reactive power regulation resources to meet the requirements of system power supply-demand balance. Finally
the proposed optimal scheduling method is analyzed and validated in the testing systems. The results show that the proposed method can achieve optimal scheduling of distributed controllable resources while improving system operation economy and flexibility.
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