Aggregation and Distributed Scheduling of Multi-type Flexibility Resources Including Electric Vehicles

XIE Haixiang; GAO Shan; ZHENG Junyi; HUANG Xueliang

doi:10.7500/AEPS20250901004

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Aggregation and Distributed Scheduling of Multi-type Flexibility Resources Including Electric Vehicles

Basic Research | 更新时间：2026-10-11

- Aggregation and Distributed Scheduling of Multi-type Flexibility Resources Including Electric Vehicles
- Automation of Electric Power Systems Vol. 50, Pages: 80-92(2026)
- 作者机构：
  
  东南大学电气工程学院，江苏省南京市 210096
- 作者简介：
- 基金信息：
  
  Jiangsu Provincial Science and Technology Innovation Special Fund for Carbon Peak and Carbon Neutrality(BE2022030-2)
- DOI：10.7500/AEPS20250901004
  CLC：
- Received：01 September 2025，
  
  Revised：2026-01-28，
  
  Online First：23 April 2026，
  
  Published：25 November 2026
- 稿件说明：
移动端阅览
解海翔,高山,郑隽一等.含电动汽车的多类型灵活性资源聚合与分布式调度[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250901004.

XIE Haixiang,GAO Shan,ZHENG Junyi,et al.Aggregation and Distributed Scheduling of Multi-type Flexibility Resources Including Electric Vehicles[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250901004.
解海翔,高山,郑隽一等.含电动汽车的多类型灵活性资源聚合与分布式调度[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250901004. DOI：

XIE Haixiang,GAO Shan,ZHENG Junyi,et al.Aggregation and Distributed Scheduling of Multi-type Flexibility Resources Including Electric Vehicles[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250901004. DOI：

摘要

针对当前多类型灵活性资源在聚合建模与调度中仍面临可行域描述不统一、集中式调度框架协同效率低及不确定性处理保守等问题，文中提出一种基于改进列生成的Dantzig-Wolfe分解(Dantzig-Wolfe decomposition-column generation

DWD-CG)算法的分布式调度框架，以实现多类型灵活性资源的统一聚合建模与高效协同求解。首先，基于Minkowski和的方法建立电动汽车聚合可行域，并据此扩展实现适应电动汽车、温控负荷和需求响应负荷集群的多类型灵活性资源的统一聚合表达；其次，针对电动汽车集群类型比例波动问题，构建了数据驱动的范数不确定性描述；针对分布式光伏出力的随机波动问题，引入有限样本下分布鲁棒机会约束的最劣下界建模。进一步，基于多灵活性主体交互框架，提出“聚合商-集群”两层协同优化模型，并给出DWD-CG算法的分布式求解策略。算例结果表明，所提框架在保证鲁棒可行性的同时，较传统方法具有更优的运行成本表现，并提升了求解效率与可扩展性。

Abstract

To address the existing challenges in aggregation modeling and scheduling of multi-type flexibility resources—such as non-unified descriptions of feasible regions

low coordination efficiency of centralized scheduling frameworks

and conservative uncertainty handling—this paper proposes a distributed scheduling framework based on an improved Dantzig-Wolfe decomposition-column generation (DWD-CG) algorithm

enabling unified aggregation modeling and efficient collaborative optimization of multi-type flexibility resources. First

the Minkowski-sum method is adopted to construct the aggregated feasible region of electric vehicle (EV) clusters

which is further extended to achieve a unified aggregation representation for multiple types of flexibility resources. Second

to describe fluctuations in the proportion of different categories resulting from the electric vehicles clustering

a data-driven norm-based uncertainty set is constructed; to handle the stochastic fluctuation of distributed photovoltaic (PV) generation

a distributionally robust chance-constrained model with a worst-case lower bound under finite samples is introduced. Furthermore

based on the multi-flexibility-entity interaction framework

a two-layer aggregator-cluster collaborative optimization model is formulated

and a distributed solving strategy based on the DWD-CG algorithm is provided. Case studies demonstrate that the proposed framework ensures robust feasibility while achieving better operating cost performance

and achieves higher computational efficiency and scalability compared with conventional methods.

关键词

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references

习近平主持召开中央财经委员会第九次会议［EB/OL］.［ 2021-08-26 ］. http：//www.gov.cn/xinwen/2021-03/15/content_5593154.htm http://www.gov.cn/xinwen/2021-03/15/content_5593154.htm .

Xi Jinping presided over the ninth meeting of the central committee on finance and economics ［EB/OL］. ［ 2021-08-26 ］. http：//www.gov.cn /xinwen/2021-03/15/content_5593154.htm http://www.gov.cn/xinwen/2021-03/15/content_5593154.htm .

梁歆怡，尤作为，林凌雪 . 终端电气化驱动的城市电力消费演化路径研究［J］. 电力系统及其自动化学报， 2025 ， 37 （ 10 ）： 1 - 12 .

Liang Xinyi ， You Zuowei ， Lin Lingxue . Research on evolutionary path of urban electricity consumption driven by end-use electrification ［J］. Proceedings of the CSU-EPSA ， 2025 ， 37 （ 10 ）： 1 - 12 .

陈郑平，李文忠，陈飞雄，等 . 分布式资源助力新型电力系统灵活性提升研究综述［J］. 电力工程技术， 2025 ， 44 （ 2 ）： 145 - 159 .

Chen Zhengping ， Li Wenzhong ， Chen Feixiong ， et al . Summary of research on improving the flexibility of new power systems with distributed resources ［J］. Jiangsu Electrical Engineering ， 2025 ， 44 （ 2 ）： 145 - 159 .

范宏，盛哲祺，张树卿 . 分布式灵活性资源的动态聚合调控与协同效益分配研究综述［J］. 浙江电力， 2025 ， 44 （ 9 ）： 30 - 45 .

Fan Hong ， Sheng Zheqi ， Zhang Shuqing . Review on dynamic aggregation control and collaborative benefit allocation of distributed flexibility resources ［J］. Zhejiang Electric Power ， 2025 ， 44 （ 9 ）： 30 - 45 .

Xu M S ， Gao S ， Zheng J Y ， et al . Day-ahead electric vehicle charging behavior forecasting and schedulable capacity calculation for electric vehicle parking lot ［J］. Energy ， 2024 ， 309 ： 133090 .

王珂，李玮桁，王正风，等 . 基于两阶段鲁棒优化的电动汽车可调容量聚合及解聚方法［J］. 电力系统自动化， 2025 ， 49 （ 24 ）： 115 - 124 .

Wang Ke ， Li Weiheng ， Wang Zhengfeng ， et al . Adjustable capacity aggregation and disaggregation method for electric vehicles based on two-stage robust optimization ［J］. Automation of Electric Power Systems ， 2025 ， 49 （ 24 ）： 115 - 124 .

杨婷，朱晓，陆旦宏，等 . 计及场景互动意愿的定变频空调群优化调控［J］. 电力工程技术， 2025 ， 44 （ 2 ）： 197 - 208 .

Yang Ting ， Zhu Xiao ， Lu Danhong ， et al . Optimal control for fixed and inverter air conditioning groups considering interaction willingness in scenarios ［J］. Jiangsu Electrical Engineering ， 2025 ， 44 （ 2 ）： 197 - 208 .

Wang G R ， Li Z S ， Wang F . Enhanced sufficient battery model for aggregate flexibility of thermostatically controlled loads considering coupling constraints ［J］. IEEE Transactions on Sustainable Energy ， 2021 ， 12 （ 4 ）： 2493 - 2496 .

包诗媛，雷星雨，居来提·阿不力孜，等 . 考虑非凸运行特性的多能源系统灵活调节能力刻画与聚合［J］. 电力系统自动化， 2023 ， 47 （ 15 ）： 55 - 66 .

Bao Shiyuan ， Lei Xingyu ， Abulizi Julaiti ， et al . Depiction and aggregation for flexible regulation capability of multi-energy system considering nonconvex operation characteristics ［J］. Automation of Electric Power Systems ， 2023 ， 47 （ 15 ）： 55 - 66 .

王静，刘牧阳，陈俊儒，等 . 基于凸多面体仿射变换的用户侧灵活性资源多元聚合方法［J/OL］. 电网技术， 2025-08-25 . https：//doi.org/10.13335/j.1000-3673.pst.2024.1595 https://doi.org/10.13335/j.1000-3673.pst.2024.1595 .

Wang Jing ， Liu Muyang ， Chen Junru ， et al . Research on multi-resources aggregation methods of user-side flexibility resources based on affine transformations of convex polytope ［J/OL］. Power System Technology ， 2025-08-25 . https：//doi.org/10.13335/j.1000-3673.pst.2024.1595 https://doi.org/10.13335/j.1000-3673.pst.2024.1595 .

赵明欣，丁保迪，吴一恒，等 . 基于保守度自适应优化的综合能源系统鲁棒灵活性评估［J］. 电网技术， 2025 ， 49 （ 2 ）： 582 - 592 .

Zhao Mingxin ， Ding Baodi ， Wu Yiheng ， et al . Robust flexibility evaluation of integrated energy systems based on conservatism adaptive optimization ［J］. Power System Technology ， 2025 ， 49 （ 2 ）： 582 - 592 .

Contreras D A ， Rudion K . Computing the feasible operating region of active distribution networks： comparison and validation of random sampling and optimal power flow based methods ［J］. IET Generation ， Transmission & Distribution， 2021 ， 15 （ 10 ）： 1600 - 1612 .

李懿鑫，李正烁 . 考虑恶意攻击和随机性注入的配电网-聚合商双层灵活性评估方法［J/OL］. 中国电机工程学报， 2026-01-27 . https：//link.cnki.net/urlid/11.2107.TM.20250724.1433.006 https://link.cnki.net/urlid/11.2107.TM.20250724.1433.006 .

Li Yixin ， Li Zhengshuo . A distribution network-aggregator two-layer flexibility evaluation method considering malicious attacks and stochastic injections ［J/OL］. Proceedings of the CSEE ， 2026-01-27 . https：//link.cnki.net/urlid/11.2107.TM.20250724.1433.006 https://link.cnki.net/urlid/11.2107.TM.20250724.1433.006 .

张梓麒，陈中 . 主动配电网多元主体灵活性和随机性的转换机制与刻画方法［J］. 电力系统自动化， 2024 ， 48 （ 13 ）： 79 - 88 .

Zhang Ziqi ， Chen Zhong . Transformation mechanisms and characterization methods for flexibility and uncertainty in active distribution networks with multiple entities ［J］. Automation of Electric Power Systems ， 2024 ， 48 （ 13 ）： 79 - 88 .

姚倩倩，李新皓 . 含高比例分布式资源的乡村配电系统有功-无功协同优化调控方法［J］. 电力大数据， 2024 ， 27 （ 9 ）： 19 - 30 .

Yao Qianqian ， Li Xinhao . Active-reactive power coordinated optimization control method of rural power distribution system with high proportion of distributed resources ［J］. Power Systems and Big Data ， 2024 ， 27 （ 9 ）： 19 - 30 .

杨宏坤，王旭，蒋传文，等 . 分布式资源聚合可行和频率稳定约束下输配网协同灾前调度［J］. 电力系统自动化， 2025 ， 49 （ 16 ）： 52 - 61 .

Yang Hongkun ， Wang Xu ， Jiang Chuanwen ， et al . Coordinated pre-disaster scheduling of transmission and distribution networks under aggregation feasibility and frequency stability constraints of distributed energy resources ［J］ . Automation of Electric Power Systems ， 2025 ， 49 （ 16 ）： 52 - 61 .

Zhao J X ， Zhai Q Z ， Zhou Y Z ， et al . Adaptive characteristic modeling of long-period uncertainties： a multi-stage robust energy storage planning approach based on the finite covering theorem ［J］. IEEE Transactions on Sustainable Energy ， 2024 ， 15 （ 4 ）： 2393 - 2404 .

Liu X ， Li Y ， Wang L ， et al . Dynamic aggregation strategy for a virtual power plant to improve flexible regulation ability ［J］. Energy ， 2024 ， 297 ： 131261 .

刘维民，肖辉，曾林俊，等 . 考虑电动汽车充电模式和供需灵活性的综合能源系统优化调度［J］. 电力建设， 2025 ， 46 （ 6 ）： 1 - 12 .

Liu Weimin ， Xiao Hui ， Zeng Linjun ， et al . Optimal scheduling of integrated energy systems considering electric vehicle charging patterns and supply-demand flexibility ［J］. Electric Power Construction ， 2025 ， 46 （ 6 ）： 1 - 12 .

Yu Z P ， Lin J ， Liu F ， et al . Joint multi-stage planning of renewable generation， HESS， and AESS for deeply decarbonizing power systems with high-penetration renewables ［J］. IEEE Transactions on Sustainable Energy ， 2025 ， 16 （ 3 ）： 1613 - 1628 .

Huo X ， Huang H ， Davis K R ， et al . A review of scalable and privacy-preserving multi-agent frameworks for distributed energy resources ［J］. Advances in Applied Energy ， 2025 ， 17 ： 100205 .

赵海兵，封国栋，高文浩，等 . 大规模区域型微网集群的去中心调度［J］. 电测与仪表， 2022 ， 59 （ 9 ）： 84 - 92 .

Zhao Haibing ， Feng Guodong ， Gao Wenhao ， et al . Decentralized scheduling of large-scale regional micro-grid clusters ［J］. Electrical Measurement & Instrumentation ， 2022 ， 59 （ 9 ）： 84 - 92 .

黄启文，陆文甜，刘明波 . 随机动态经济调度问题的Dantzig-Wolfe分解及其并行算法［J］. 电网技术， 2019 ， 43 （ 12 ）： 4398 - 4406 .

Huang Qiwen ， Lu Wentian ， Liu Mingbo . Dantzig-Wolfe decomposition and parallel algorithm for stochastic dynamic economic dispatch ［J］. Power System Technology ， 2019 ， 43 （ 12 ）： 4398 - 4406 .

詹祥澎，杨军，韩思宁，等 . 考虑电动汽车可调度潜力的充电站两阶段市场投标策略［J］. 电力系统自动化， 2021 ， 45 （ 10 ）： 86 - 96 .

Zhan Xiangpeng ， Yang Jun ， Han Sining ， et al . Two-stage market bidding strategy of charging station considering schedulable potential capacity of electric vehicle ［J］. Automation of Electric Power Systems ， 2021 ， 45 （ 10 ）： 86 - 96 .

Xie H X ， Gao S ， Zheng J Y ， et al . A three-stage robust dispatch model considering the multi-uncertainties of electric vehicles and a multi-energy microgrid ［J］. International Journal of Electrical Power & Energy Systems ， 2024 ， 157 ： 109778 .

黄红选，韩继业 . 数学规划［M］. 北京：清华大学出版社， 2006 .

Huang Hongxuan ， Han Jiye . Mathematical programming ［M］. Beijing ： Tsinghua University Press ， 2006 .

Mcnamara P ， Mcloone S . Hierarchical demand response for peak minimization using Dantzig-Wolfe decomposition ［J］. IEEE Transactions on Smart Grid ， 2015 ， 6 （ 6 ）： 2807 - 2815 .

汪进锋，田野，江霖，等 . 计及碳-绿证市场耦合的新能源和储能虚拟惯量-阻尼调度方法［J］. 广东电力， 2025 ， 38 （ 8 ）： 80 - 90 .

Wang Jinfeng ， Tian Ye ， Jiang Lin ， et al . Optimal virtual inertia-damping scheduling method for renewable energy and energy storage considering carbon-green certificate market coupling ［J］. Guangdong Electric Power ， 2025 ， 38 （ 8 ）： 80 - 90 .

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