基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法

蔡木良; 赖信辉; 李赢正; 田野; 余杰; 程敏军; 许银亮; 蔺晨晖

doi:10.11930/j.issn.1004-9649.202505069

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基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法

考虑分布式虚拟储能聚合的综合能源系统规划、运行和交易的关键技术 | 更新时间：2026-02-03

- 基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法
- Power-carbon-green certificate distributed cooperative optimization method based on flexibility support mechanism of active distribution networks
- 中国电力 2026年59卷第1期页码：10-19
- 作者机构：
  
  1. 国网江西省电力有限公司电力科学研究院,江西,南昌,330096
  2. 清华大学深圳国际研究生院,广东,深圳,518000
  3. 国网江西省电力有限公司,江西,南昌,330096
  4. 国网江西省电力有限公司鹰潭供电分公司,江西,鹰潭,335000
  5. 清华大学电机工程与应用电子技术系,北京,100084
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（52307101）;2024年国网江西电力重点研究科技项目（521820240022）。
- DOI：10.11930/j.issn.1004-9649.202505069
  中图分类号：
- 网络出版：2026-01-13，
  
  纸质出版：2026-01-13
- 稿件说明：
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蔡木良, 赖信辉, 李赢正, 田野, 余杰, 程敏军, 许银亮, 蔺晨晖. 基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法[J]. 中国电力, 2026, 59(1): 10-19.

蔡木良, 赖信辉, 李赢正, et al. Power-carbon-green certificate distributed cooperative optimization method based on flexibility support mechanism of active distribution networks[J]. 2026, 59(1): 10-19.
蔡木良, 赖信辉, 李赢正, 田野, 余杰, 程敏军, 许银亮, 蔺晨晖. 基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法[J]. 中国电力, 2026, 59(1): 10-19. DOI： 10.11930/j.issn.1004-9649.202505069.

蔡木良, 赖信辉, 李赢正, et al. Power-carbon-green certificate distributed cooperative optimization method based on flexibility support mechanism of active distribution networks[J]. 2026, 59(1): 10-19. DOI： 10.11930/j.issn.1004-9649.202505069.

摘要

随着分布式新能源和电动汽车等虚拟储能的广泛接入，电力系统的不确定性和低惯量特性变得更加显著，系统的频率运行风险增加，并且主动配电网内部的供需关系呈现出更加灵活多样的特征，导致其与输电网之间的功率交互关系也更加复杂。为此，构建了一种基于主动配电网灵活性支撑机制的电-碳-绿证分布式协同优化方法，以充分挖掘输配系统中分布式资源的支撑能力及其碳减排效益。首先，建立了与输配协同系统匹配的动态频率安全约束和基于双向调节模型的主动配电网灵活性支撑机制，提出了输配系统间的电-碳-绿证协同交互框架。为应对新能源出力的不确定性，将两侧子系统中涉及不确定变量的约束建模为联合机会约束。采用交替方向乘子法（alternating direction of multipliers algorithm，ADMM）进行输配系统的分布式协同。仿真结果表明，所提模型能够有效挖掘配电网中分布式资源的支撑潜力，灵活体现主动配电网的向外支撑能力或被支撑需求。与传统方法相比，系统动态频率安全性和输配协同调节灵活性显著提升，总运行成本较输电网单独调度模型降低13.42%，新能源减载量较忽略多市场耦合模型减少16.76%，系统运行经济性和低碳性明显改善。此外，所提出的求解方法比基于传统的样本平均近似方法减少约98%的计算时间，能够实现输配系统的快速分布式协同优化。

Abstract

The widespread integration of distributed renewable energy sources and virtual energy storage

such as electric vehicles

exacerbates the inherent uncertainty and low-inertia characteristics of power systems

thereby heightening frequency violation risks. Concurrently

the increasing flexibility and diversity of supply-demand dynamics within active distribution networks (ADNs) further complicate their interactions with transmission grids. To address these challenges

this paper proposes a novel power-carbon-green certificate distributed cooperative optimization framework based on the flexibility support mechanism of ADNs

with the objective of maximizing the utilization of distributed regulation resources and enhancing carbon reduction potential within integrated transmission-distribution (ITD) systems. Firstly

the dynamic frequency security constraints tailored to ITD systems and a flexibility support mechanism for ADNs based on interactive regulation modeling are established

forming a comprehensive ITD electricity-carbon-green certificate cooperation framework. To effectively address the uncertainty inherent in subsystems

joint chance constraints (JCCs) are employed to model the probabilistic nature of the problem. The Alternating direction of multipliers algorithm (ADMM) algorithm is adopted for the distributed cooperation of the transmission and distribution system. Case studies demonstrate the effectiveness of the proposed method in fully leveraging distributed resources and enhancing system frequency security. The framework also exhibits the ability to flexibly reflect the external support capacity or supported demand of ADNs. Compared to the transmission-grid independent dispatch model

the total operation cost is reduced by 13.42%

while renewable energy curtailment is decreased by 16.76% relative to the model that ignores multi-market coupling. These results demonstrate significant improvements in both the operational economy and low-carbon performance of the system. Furthermore

the proposed method achieves a reduction of approximately 98% in computational time compared to the traditional sample-average approximation (SAA)-based approach

thereby facilitating rapid distributed coordination within ITD systems.

关键词

Keywords

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