计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度

王泽森; 王宣元; 孔帅皓; 孙舶皓; 季震; 孙巍

doi:10.11930/j.issn.1004-9649.202508039

欢迎来到能源电力期刊网！

您当前的位置：

首页 >

文章列表页 >

计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度

电-碳协同下分布式能源系统运营关键技术 | 更新时间：2026-03-17

- 计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度
- Coordinated dispatch of virtual power plant and distribution network considering multi-time scale carbon emission factors
- 中国电力 2026年59卷第3期页码：14-26
- 作者机构：
  
  国网冀北电力有限公司,北京,100054
- 作者简介：
- 基金信息：
  
  国网冀北电力有限公司科技项目（52018K25000T）。
- DOI：10.11930/j.issn.1004-9649.202508039
  中图分类号：
- 网络首发：2026-03-16，
  
  纸质出版：2026-03-16
- 稿件说明：
移动端阅览
王泽森, 王宣元, 孔帅皓, 孙舶皓, 季震, 孙巍. 计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度[J]. 中国电力, 2026, 59(3): 14-26.

WANG Zesen, WANG Xuanyuan, KONG Shuaihao, et al. Coordinated dispatch of virtual power plant and distribution network considering multi-time scale carbon emission factors[J]. 2026, 59(3): 14-26.
王泽森, 王宣元, 孔帅皓, 孙舶皓, 季震, 孙巍. 计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度[J]. 中国电力, 2026, 59(3): 14-26. DOI： 10.11930/j.issn.1004-9649.202508039.

WANG Zesen, WANG Xuanyuan, KONG Shuaihao, et al. Coordinated dispatch of virtual power plant and distribution network considering multi-time scale carbon emission factors[J]. 2026, 59(3): 14-26. DOI： 10.11930/j.issn.1004-9649.202508039.

摘要

随着双碳目标的推进，电力系统的低碳化运行成为研究热点，虚拟电厂与配电网的协同调度面临多时间尺度碳排放量化不足的挑战。为此，提出一种计及多时间尺度碳排放因子的虚拟电厂-配电网协同调度模型。首先，将新能源弃风弃光现象考虑到碳排放因子计算中，并通过多时间尺度修正机制提升碳排放因子的时空精度。其次，构建粗调-细调的多时间尺度协同调度框架：日前调度以经济性和安全性为目标，日内调度基于实时数据修正碳排放因子并优化运行策略。最后，采用目标级联分析法求解模型。算例分析表明，改进的碳排放因子能有效区分零碳时段的风光消纳差异，相比传统碳排放因子计算方法使配电网碳排放量减少4.7t，碳排放成本下降17.5%。多时间尺度协同机制显著提升了新能源消纳能力与经济性，为电力系统低碳调度提供了有力支持。

Abstract

With the advancement of dual-carbon goals

the low-carbon operation of power systems has become a research focus. However

the coordinated dispatch between virtual power plants (VPPs) and distribution networks (DNs) faces challenges due to insufficient multi-time scale carbon emission quantification. To address this issue

this paper proposes a coordinated dispatch model for VPPs and DNs that incorporates multi-time scale carbon emission factors. First

the phenomenon of renewable energy curtailment is integrated into the carbon emission factor calculation

and a multi-time scale correction mechanism is introduced to enhance the spatiotemporal accuracy of the carbon emission factors. Second

a coarse-fine tuning multi-time scale coordinated dispatch framework is established: the day-ahead scheduling prioritizes economic efficiency and security

while the intraday scheduling adjusts carbon emission factors and optimizes operational strategies based on real-time data. Finally

the model is solved using the analytical target cascading method. Case study shows that the improved carbon emission factor can effectively differentiate the accommodation differences of wind and solar power during zero-carbon periods. Compared with traditional carbon emission factor calculation methods

it reduces the DNs' carbon emissions by 4.7 tons and cuts carbon emission costs by 17.5%. The multi-time scale coordination mechanism significantly enhances the renewable energy accommodation capacity and economic efficiency

providing strong support for low-carbon dispatch of the power system.

关键词

Keywords

references

1朱法华, 徐静馨, 潘超, 等. 煤电在碳中和目标实现中的机遇与挑战[J]. 电力科技与环保, 2022, 38 (2): 79- 86.

ZHU Fahua, XU Jingxin, PAN Chao, et al. Opportunities and challenges of coal power industry in the achievement of carbon neutrality goal[J]. Electric Power Technology and Environmental Protection, 2022, 38 (2): 79- 86.

2丁小强, 袁至, 李骥. 基于混合Wasserstein两阶段分布鲁棒的多区域含氢综合能源系统合作运行优化[J]. 中国电力, 2025, 58 (7): 1- 14.

DING Xiaoqiang, YUAN Zhi, LI Ji. Cooperative operation optimization for multi-region hydrogen-integrated integrated energy system based on hybrid Wasserstein two-stage distributionally robust[J]. Electric Power, 2025, 58 (7): 1- 14.

3马成元, 陈皓勇, 肖东亮. 考虑碳约束的新型电力系统跨区域优化调度研究[J]. 智慧电力, 2024, 52 (6): 38- 45.

MA Chengyuan, CHEN Haoyong, XIAO Dongliang. Cross-region optimal dispatch of new power system considering carbon constraints[J]. Smart Power, 2024, 52 (6): 38- 45.

4刘博洋, 秦文萍, 王杰, 等. 基于概率碳流分析的综合能源系统两阶段低碳经济调度[J]. 智慧电力, 2026, 54 (1): 1- 12.

LIU Boyang, QIN Wenping, WANG Jie, et al. Two-stage low-carbon economic dispatch for integrated energy systems based on probabilistic carbon flow analysis[J]. Smart Power, 2026, 54 (1): 1- 12.

5舒征宇, 方曼琴, 李黄强, 等. 计及季节性碳排的综合能源系统经济优化调度[J]. 智慧电力, 2025, 53 (9): 37- 47.

SHU Zhengyu, FANG Manqin, LI Huangqiang, et al. Economic optimal scheduling of integrated energy systems considering seasonal carbon emissions[J]. Smart Power, 2025, 53 (9): 37- 47.

6马欣梅, 李晓露, 柳劲松, 等. 基于移动储能与配电网协同的低碳鲁棒优化运行策略[J]. 智慧电力, 2025, 53 (8): 20- 28.

MA Xinmei, LI Xiaolu, LIU Jinsong, et al. Low-carbon robust optimization strategy for coordinated operation of mobile energy storage and distribution networks[J]. Smart Power, 2025, 53 (8): 20- 28.

7LIU 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.

8朱睿, 欧乙丁, 李筱天, 等. 基于外特性等值的虚拟电厂灵活性资源价值评估[J]. 中国电力, 2024, 57 (1): 30- 39.

ZHU Rui, OU Yiding, LI Xiaotian, et al. Evaluation of virtual power plant flexibility resources based on external characteristic equivalence[J]. Electric Power, 2024, 57 (1): 30- 39.

9LIU X, LIN X S, QIU H F, et al. Optimal aggregation and disaggregation for coordinated operation of virtual power plant with distribution network operator[J]. Applied Energy, 2024, 376, 124142.

10卫志农, 余爽, 孙国强, 等. 虚拟电厂的概念与发展[J]. 电力系统自动化, 2013, 37 (13): 1- 9.

WEI Zhinong, YU Shuang, SUN Guoqiang, et al. Concept and development of virtual power plant[J]. Automation of Electric Power Systems, 2013, 37 (13): 1- 9.

11张艺, 刘蕊. 考虑不确定性风险的虚拟电厂优化调度模型研究[J]. 智慧电力, 2024, 52 (8): 9- 18.

ZHANG Yi, LIU Rui. Virtual power plant optimal scheduling model considering uncertain risks[J]. Smart Power, 2024, 52 (8): 9- 18.

12王秋杰, 刘国安, 谭洪, 等. 考虑电氢耦合的虚拟电厂鲁棒可行域模型与求解[J]. 电网技术, 2025, 49 (3): 889- 898.

WANG Qiujie, LIU Guoan, TAN Hong, et al. Models and solutions of robust feasible region for virtual power plants with electric hydrogen coupling[J]. Power System Technology, 2025, 49 (3): 889- 898.

13徐慧慧, 田云飞, 赵宇洋, 等. 考虑绿证-碳交易的多虚拟电厂混合博弈优化调度[J]. 智慧电力, 2024, 52 (3): 1- 7, 16.

XU Huihui, TIAN Yunfei, ZHAO Yuyang, et al. Optimal scheduling of multiple virtual power plants mixed game considering green certificate and carbon trading[J]. Smart Power, 2024, 52 (3): 1- 7, 16.

14王秀云, 崔本旺. 阶梯型碳交易机制下考虑垃圾焚烧参与的虚拟电厂协调优化调度[J]. 东北电力大学学报, 2024, 44 (6): 101- 111.

WANG Xiuyun, CUI Benwang. Coordinated optimal scheduling of virtual power plants considering waste incineration participation under stepped carbon trading mechanisms[J]. Journal of Northeast Electric Power University, 2024, 44 (6): 101- 111.

15周天睿, 康重庆, 徐乾耀, 等. 电力系统碳排放流分析理论初探[J]. 电力系统自动化, 2012, 36 (7): 38- 43, 85.

ZHOU Tianrui, KANG Chongqing, XU Qianyao, et al. Preliminary theoretical investigation on power system carbon emission flow[J]. Automation of Electric Power Systems, 2012, 36 (7): 38- 43, 85.

17崔杨, 姜帅, 赵钰婷, 等. 考虑超碳需求响应的综合能源系统低碳优化调度[J]. 电网技术, 2024, 48 (5): 1863- 1872.

CUI Yang, JIANG Shuai, ZHAO Yuting, et al. Source-load coordinated carbon reduction optimal scheduling of integrated energy system considering ultra-carbon demand response[J]. Power System Technology, 2024, 48 (5): 1863- 1872.

18程昱舒, 郭晓霞, 刘青, 等. 基于动态碳排放因子的台区碳减排收益量化模型[J]. 现代电力, 2025, 42 (1): 168- 175.

CHENG Yushu, GUO Xiaoxia, LIU Qing, et al. Quantification model of carbon emission reduction benefits based on dynamic carbon emission factors in a subtation area[J]. Modern Electric Power, 2025, 42 (1): 168- 175.

19孙国强, 王力予, 周亦洲, 等. 基于对等架构的虚拟电厂-配电网双层电碳协同调度模型[J]. 电力自动化设备, 2025, 45 (1): 42- 50.

SUN Guoqiang, WANG Liyu, ZHOU Yizhou, et al. Dual-level electric-carbon coordinated scheduling model for virtual power plants and distribution networks based on equality architecture[J]. Electric Power Automation Equipment, 2025, 45 (1): 42- 50.

20钟荣豪, 张亚超, 朱蜀, 等. 基于电-碳点对点交易的虚拟电厂联盟与配电网协同低碳运行策略研究[J]. 电网技术, 2024, 48 (9): 3554- 3563.

ZHONG Ronghao, ZHANG Yachao, ZHU Shu, et al. Research on collaborative low-carbon operation strategy of electricity carbon peer-to-peer trading based virtual power plant union and power distribution network[J]. Power System Technology, 2024, 48 (9): 3554- 3563.

21刘军会, 龚健, 佟炳绅, 等. 基于分布式储能与光伏的虚拟电厂与配电网协同优化方法[J]. 中国电力, 2025, 58 (6): 1- 9.

LIU Junhui, GONG Jian, TONG Bingshen, et al. Coordinated optimization method for virtual power plants and distribution networks considering distributed energy storage and photovoltaics[J]. Electric Power, 2025, 58 (6): 1- 9.

22刘丽军, 胡鑫, 林锟, 等. 计及碳排放分摊的配电网分布式低碳调度策略[J]. 中国电机工程学报, 2024, 44 (24): 9594- 9607.

LIU Lijun, HU Xin, LIN Kun, et al. Distributed low carbon dispatch for distribution networks with carbon emission sharing[J]. Proceedings of the CSEE, 2024, 44 (24): 9594- 9607.

23葛津铭, 刘志文, 王朝斌, 等. 考虑需求响应的高比例光伏配电网低碳调度[J]. 电网技术, 2024, 48 (5): 1929- 1937.

GE Jinming, LIU Zhiwen, WANG Chaobin, et al. Low-carbon dispatching of high proportion photovoltaic distribution network considering demand response[J]. Power System Technology, 2024, 48 (5): 1929- 1937.

24邹宇航, 曾艾东, 郝思鹏, 等. 阶梯式碳交易机制下综合能源系统多时间尺度优化调度[J]. 电网技术, 2023, 47 (6): 2185- 2198.

ZOU Yuhang, ZENG Aidong, HAO Sipeng, et al. Multi-time-scale optimal dispatch of integrated energy systems under stepped carbon trading mechanism[J]. Power System Technology, 2023, 47 (6): 2185- 2198.

25GAN L W, LI N, TOPCU U, et al. Exact convex relaxation of optimal power flow in radial networks[J]. IEEE Transactions on Automatic Control, 2015, 60 (1): 72- 87.

26ZHENG W Y, WU W C, ZHANG B M, et al. A fully distributed reactive power optimization and control method for active distribution networks[J]. IEEE Transactions on Smart Grid, 2015: 1.

27YI Z K, XU Y L, ZHOU J G, et al. Bi-level programming for optimal operation of an active distribution network with multiple virtual power plants[J]. IEEE Transactions on Sustainable Energy, 2020, 11 (4): 2855- 2869.

28YANG Z F, ZHONG H W, BOSE A, et al. A linearized OPF model with reactive power and voltage magnitude: a pathway to improve the MW-only DC OPF[J]. IEEE Transactions on Power Systems, 2018, 33 (2): 1734- 1745.

29ZHANG T C, WANG J X, XIA Q, et al. Extracting umbrella constraint-based representation of local electricity markets[J]. IEEE Transactions on Smart Grid, 2023, 14 (2): 1632- 1641.

30DORMOHAMMADI S, RAIS-ROHANI M. Exponential penalty function formulation for multilevel optimization using the analytical target cascading framework[J]. Structural and Multidisciplinary Optimization, 2013, 47 (4): 599- 612.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法

碳-绿证交易机制下计及分布式储能的虚拟电厂经济性分析

德国虚拟电厂发展现状经验分析及启示

基于分布式储能与光伏的虚拟电厂与配电网协同优化方法

考虑虚拟电厂的电力系统一致性经济调度方法