历史数据驱动的综合能源系统分布式鲁棒低碳优化模型

doi:10.3969/j.issn.2097-0706.2026.03.005

综合智慧能源 ›› 2026, Vol. 48 ›› Issue (3): 47-55.doi: 10.3969/j.issn.2097-0706.2026.03.005

历史数据驱动的综合能源系统分布式鲁棒低碳优化模型

王梓璇¹(), 郝禹¹^,^*(), 刘星辰¹(), 孙韦男¹(), 刘琳¹(), 张逸²()

¹ 吉林省气象信息网络中心，长春 130062
² 国网吉林省电力有限公司长春市双阳区供电分公司，长春 130021

收稿日期:2025-05-06 修回日期:2025-06-23 出版日期:2026-03-25
通讯作者: *郝禹（1991），男，工程师，硕士，从事气象信息技术方面的研究，987068078@qq.com。
作者简介:王梓璇（1998），女，助理工程师，硕士，从事综合能源系统优化调度、气象信息技术等方面的研究，wangzxfairy98@163.com；
刘星辰（1993），女，工程师，硕士，从事综合气象信息技术方面的研究，piao_hang@163.com；
孙韦男（1996），女，工程师，硕士，从事综合气象信息技术方面的研究，ziwang7777@gmail.com；
刘琳（1985），女，高级工程师，从事气象信息技术方面的研究，850568158@qq.com；
张逸（1997），男，工程师，硕士，从事综合能源系统优化调度方面的研究，r95982388@163.com。
基金资助:
国家电网公司科技项目(5419-202155242A00)

Distributed robust low-carbon optimization model for integrated energy systems driven by historical data

WANG Zixuan¹(), HAO Yu¹^,^*(), LIU Xingchen¹(), SUN Weinan¹(), LIU Lin¹(), ZHANG Yi²()

¹ Jilin Meteorological Information Network Center， Changchun 130062， China
² Changchun Shuangyang District Power Supply Branch of State Grid Jilin Electric Power Company Limited， Changchun 130021， China

Received:2025-05-06 Revised:2025-06-23 Published:2026-03-25
Supported by:
Science and Technology Project of State Grid Corporation of China(5419-202155242A00)

摘要/Abstract

摘要：

为了有效提升综合能源系统（IES）经济效益，减少碳排放，推进氢能的高效利用，降低可再生能源出力的不确定性，提出了一种历史数据驱动的IES分布式鲁棒低碳优化模型。采用数据驱动的不确定性量化方法，基于可再生能源出力的历史数据构建1-范数与∞-范数联合约束的概率分布模糊集，通过搜索最恶劣场景概率分布，构建min-max-min三层分布式鲁棒优化框架，在保障鲁棒性的同时降低调度保守性；采用集成阶梯式碳交易机制、电制氢（P2G）技术，通过分阶段碳价激励碳减排，实现系统内碳元素的闭环利用，兼顾环境效益与经济成本；最后，采用列与约束生成（C&CG）算法求解该分布式鲁棒模型。结果表明，基于混合范数模糊集所得的单日碳交易成本相比于单一范数模糊集的低1.6%左右，进一步降低了可再生能源出力模型的保守性；同时，在合理划分阶梯区间的情况下，碳排放量与碳交易成本分别下降了16.35%和22.35%，达到碳排放和碳交易成本的相对平衡。试验结果验证了该模型在降低碳交易成本方面的优势，所提模型为IES的规划与运行提供了理论支撑与实践参考。

关键词: 综合能源系统, 分布式鲁棒, 阶梯式碳交易机制, 可再生能源, 碳排放, 碳交易成本, 联合约束

Abstract:

To effectively improve the economic benefits of integrated energy systems （IES）， reduce carbon emissions， promote the efficient utilization of hydrogen energy， and mitigate the uncertainty of renewable energy output， a distributed robust low-carbon optimization model for IES driven by historical data was proposed. A data-driven uncertainty quantification method was used to construct a probability distribution ambiguity set with joint constraints of 1-norm and ∞-norm based on historical renewable energy output data. By identifying the worst-case probability distribution scenario， a min-max-min three-layer distributed robust optimization framework was constructed， ensuring robustness while reducing scheduling conservatism. An integrated tiered carbon trading mechanism and power-to-gas （P2G） technology were adopted to incentivize carbon reduction through phased carbon pricing， achieving closed-loop utilization of carbon elements within the system while balancing environmental benefits and economic costs. The distributed robust model was solved using the column-and-constraint generation （C&CG） algorithm. The results showed that the daily carbon trading cost obtained based on the hybrid-norm ambiguity set was approximately 1.6% lower than that derived from the single-norm ambiguity set， further reducing the conservatism of the renewable energy output model. Meanwhile， with a reasonable division of tiered intervals， carbon emissions and carbon trading costs were reduced by 16.35% and 22.35%， respectively， achieving a relative balance between carbon emissions and carbon trading costs. The experimental results verified the advantage of the model in reducing carbon trading costs. The proposed model provides theoretical support and practical reference for the planning and operation of IES.

Key words: integrated energy system, distributed robustness, tiered carbon trading mechanism, renewable energy, carbon emission, carbon trading cost, joint constraints

中图分类号:

TK 01：TM 73

王梓璇, 郝禹, 刘星辰, 孙韦男, 刘琳, 张逸. 历史数据驱动的综合能源系统分布式鲁棒低碳优化模型[J]. 综合智慧能源, 2026, 48(3): 47-55.

WANG Zixuan, HAO Yu, LIU Xingchen, SUN Weinan, LIU Lin, ZHANG Yi. Distributed robust low-carbon optimization model for integrated energy systems driven by historical data[J]. Integrated Intelligent Energy, 2026, 48(3): 47-55.

图/表 12

图1

表1

表2

表3

表4

图2

图3

图4

表5

表6

表7

表8

参考文献 27

[1]	彭乐瑶, 马刚, 陈永华, 等. 考虑碳交易体系的微电网多阶段鲁棒优化运行[J]. 综合智慧能源, 2024, 46(9): 9-19. doi: 10.3969/j.issn.2097-0706.2024.09.002
	PENG Leyao, MA Gang, CHEN Yonghua, et al. Multi-stage robust optimization operation of microgrids considering carbon trading systems[J]. Integrated Intelligent Energy, 2024, 46(9): 9-19. doi: 10.3969/j.issn.2097-0706.2024.09.002
[2]	WU Z N, LI Z X, YANG H. Day-ahead optimal scheduling for integrated energy system considering dynamic pipe network delay[J]. Electrical Engineering, 2024, 106(5): 6359-6372. doi: 10.1007/s00202-024-02367-y
[3]	季振亚, 郑帅帅, 许金星, 等. 计及碳-绿证联合交易的含需求响应的综合能源系统调度[J]. 综合智慧能源, 2025, 47(5): 41-50. doi: 10.3969/j.issn.2097-0706.2025.05.005
	JI Zhenya, ZHENG Shuaishuai, XU Jinxing, et al. Scheduling of integrated energy system with demand response considering carbon-green certificate joint trading[J]. Integrated Intelligent Energy, 2025, 47(5): 41-50. doi: 10.3969/j.issn.2097-0706.2025.05.005
[4]	SU B H, WANG R Q, WANG M, et al. Low-carbon economic dispatch of integrated energy systems in industrial parks considering comprehensive demand response and multi-hydrogen supply[J]. Applied Sciences-Basel, 2024, 14(6):14062381.
[5]	张力, 金立, 任炬光, 等. 计及气象因素与分时电价影响的综合能源系统负荷调控策略研究[J]. 综合智慧能源, 2024, 46(1): 18-27. doi: 10.3969/j.issn.2097-0706.2024.01.003
	ZHANG Li, JIN Li, REN Juguang, et al. Research on load regulation strategy of integrated energy systems considering meteorological factors and time-of-use tariffs[J]. Integrated Intelligent Energy, 2024, 46(1): 18-27. doi: 10.3969/j.issn.2097-0706.2024.01.003
[6]	YU P, WANG S, WANG R, et al. Robust optimal scheduling of integrated energy system considering flexible load and uncertainty[C]//2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP). IEEE, 2024:1414-1418.
[7]	HOU H, GE X D, YAN Y L, et al. An integrated energy system "green-carbon" offset mechanism and optimization method with Stackelberg game[J]. Energy, 2024, 294:130617. doi: 10.1016/j.energy.2024.130617
[8]	曾文帅, 谢经炜, 曾林俊, 等. 考虑阶梯负碳交易与生物质燃气的综合能源系统低碳优化[J]. 电力科学与工程, 2024, 40(10): 42-57.
	ZENG Wenshuai, XIE Jingwei, ZENG Linjun, et al. Low carbon optimization of integrated energy system considering ladder-type negative carbon trading and biomass gas[J]. Electric Power Science and Engineering, 2024, 40(10): 42-57.
[9]	陈静, 盛铭真, 张岩, 等. 考虑源荷双侧需求响应和氢能多元利用的综合能源系统低碳经济优化[J]. 广东电力, 2025, 38(1): 18-31.
	CHEN Jing, SHENG Mingzhen, ZHANG Yan, et al. Low carbon economic optimization of integrated energy systems considering dual demand response of source and load and multiple utilization of hydrogen energy[J]. Guangdong Electric Power, 2025, 38(1): 18-31.
[10]	封龙, 梁绍华, 邹磊, 等. 基于改进粒子群算法的变工况综合能源系统优化调度[J]. 电气自动化, 2025, 47(1): 16-19, 22.
	FENG Long, LIANG Shaohua, ZOU Lei, et al. Optimized scheduling of variable condition integrated energy system based on improved particle swarm optimization algorithm[J]. Electrical Automation, 2025, 47(1): 16-19, 22.
[11]	江美慧, 许镇江, 张其朴, 等. 面向综合能源系统的综合需求响应策略及其建模技术[J]. 电力建设, 2024, 45(12): 65-82.
	JIANG Meihui, XU Zhenjiang, ZHANG Qipu, et al. Integrated demand response strategy and modeling technology for integrated energy systems[J]. Electric Power Construction, 2024, 45(12): 65-82.
[12]	江训谱, 包哲静, 于淼, 等. 考虑源荷不确定性的园区综合能源系统鲁棒多阶段规划[J]. 电力建设, 2025, 46(4): 99-112.
	JIANG Xunpu, BAO Zhejing, YU Miao, et al. Robust multi-stage planning of park-level integrated energy system considering source-load uncertainties[J]. Electric Power Construction, 2025, 46(4): 99-112.
[13]	徐睿婕, 任永峰, 祝荣, 等. 基于绿证-碳交易交互机制与合作博弈理论的IES系统低碳经济调度[J]. 太阳能学报, 2024, 45(9): 91-100.
	XU Ruijie, REN Yongfeng, ZHU Rong, et al. Low carbon economic dispatch of IES based on green certificate-carbon trading interaction mechanism and cooperative game theory[J]. Acta Energiae Solaris Sinica, 2024, 45(9): 91-100.
[14]	李子晨, 夏杨红, 孙勇, 等. 考虑氢能长短周期储能特性的电氢综合能源系统容量配置方法[J]. 电网技术, 2025, 49(1): 12-21.
	LI Zichen, XIA Yanghong, SUN Yong, et al. Optimal sizing of electricity-hydrogen integrated energy system considering multi-timescale operation of hydrogen storage system[J]. Power System Technology, 2025, 49(1): 12-21.
[15]	SABOORI H, HEMMATI R. Considering carbon capture and storage in electricity generation expansion planning[J]. IEEE Transactions on Sustainable Energy, 2016, 7(4): 1371-1378. doi: 10.1109/TSTE.2016.2547911
[16]	李志伟, 赵雨泽, 吴培, 等. 基于制氢设备精细建模的综合能源系统绿氢蓝氢协调低碳优化策略[J]. 电网技术, 2024, 48(6): 2317-2326.
	LI Zhiwei, ZHAO Yuze, WU Pei, et al. Low-carbon dispatching strategy of integrated energy system with coordination of green hydrogen and blue hydrogen based on fine modeling of hydrogen production equipment[J]. Power System Technology, 2024, 48(6): 2317-2326.
[17]	夏晓荣, 杨宇, 刘勇, 等. 电-气综合能源系统的分布式最优调度方法[J]. 电网与清洁能源, 2025, 41(2): 60-66, 74.
	XIA Xiaorong, YANG Yu, LIU Yong, et al. A distributed optimal dispatch method for electricity-gas integrated energy systems[J]. Power System and Clean Energy, 2025, 41(2): 60-66, 74.
[18]	ZHANG J L, LIU Z Y. Low carbon economic scheduling model for a park integrated energy system considering integrated demand response, ladder-type carbon trading and fine utilization of hydrogen[J]. Energy, 2024, 290:130311. doi: 10.1016/j.energy.2024.130311
[19]	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.
[20]	王利猛, 张逸, 曲洋. 基于阶梯式碳交易机制与细化电转气和碳循环综合能源系统优化调度[J]. 现代电力, 2024, 41(2): 335-343.
	WANG Limeng, ZHANG Yi, QU Yang. Optimal dispatch of integrated energy system based on stepped carbon trading mechanism and refined electricity-to-gas and carbon cycle[J]. Modern Electric Power, 2024, 41(2): 335-343.
[21]	MA Y H, HAN D, LU Z X. Optimal multi-timescale scheduling of integrated energy systems with hybrid energy storage system based on Lyapunov optimization[J]. Journal of Beijing Institute of Technology, 2024, 33(5): 465-480.
[22]	李亚峰, 王维庆. 考虑阶梯碳交易机制的含混氢天然气综合能源系统容量配置[J]. 电力科学与技术学报, 2023, 38(6): 237-247.
	LI Yafeng, WANG Weiqing. Capacity allocation of hydrogen-blended natural gas integrated energy system considering ladder carbon trading mechanism[J]. Journal of Electric Power Science and Technology, 2023, 38(6): 237-247.
[23]	赵振宇, 任旭. 考虑动态能价及碳证交易的综合能源系统零碳优化[J]. 电力建设, 2024, 45(8): 36-50. doi: 10.12204/j.issn.1000-7229.2024.08.004
	ZHAO Zhenyu, REN Xu. Zero-carbon optimization of integrated energy system considering dynamic energy prices and carbon certificate trading[J]. Electric Power Construction, 2024, 45(8): 36-50. doi: 10.12204/j.issn.1000-7229.2024.08.004
[24]	束娜, 江山, 刘春伶, 等. 计及灵活性资源多时间尺度协调互济的电-气-热综合能源系统优化调度[J]. 电力建设, 2024, 45(12): 3-15.
	SHU Na, JIANG Shan, LIU Chunling, et al. Optimal scheduling of electricity-gas-heat integrated energy system with flexible resources in multiple time scales[J]. Electric Power Construction, 2024, 45(12): 3-15.
[25]	夏佳伟, 张一帆, 雷浩, 等. 考虑高效氢能利用和碳捕集的综合能源系统低碳优化调度[J]. 电力建设, 2024, 45(12): 100-111.
	XIA Jiawei, ZHANG Yifan, LEI Hao, et al. Low-carbon economic dispatch of integrated energy system considering efficient hydrogen utilization and carbon capture equipment[J]. Electric Power Construction, 2024, 45(12): 100-111.
[26]	PAN Y, WANG M S, YUAN X D, et al. Optimal operation method for electricity-heat integrated energy system considering vulnerability prevention[J]. Journal of Energy Engineering, 2023, 149(6): 4886.
[27]	郝浩伟, 周博文, 张馨文. 计及碳交易与需求响应的综合能源系统优化研究[J]. 东北电力技术, 2022, 43(10):32-37.
	HAO Haowei, ZHOU Bowen, ZHANG Xinwen. Research of integrated energy system optimization considering carbon trading and demand response[J]. Northeast Electric Power Technology, 2022, 43(10):32-37.

耗电型模型参数			耗气型模型参数
a₁	b₁	c₁	a₂	b₂	c₂
36	-0.38	0.003 4	3	-0.004	0.001

设备	容量/kW	转换效率/%	爬坡约束/%
EL	500	87	20
MR	250	60	20
HFC	250	95	20
GB	800	95	20
CHP系统	600	92	20
CCS系统	250	60	20

参数	模式1	模式2	模式3
碳排放量/kg	12 758	10 671	25 792
碳交易成本/元	6 379	4 953	16 197
购电成本/元	2 408	2 822	2 379
购气成本/元	7 740	7 538	9 410
弃风成本/元	0	0	0
弃光成本/元	0	0	0
碳捕集成本/元	512	502	0
总成本/元	17 039	15 815	27 986

场景	总成本
场景	模式1	模式2	模式3
1	17 652	15 659	28 698
2	17 571	15 818	28 532
3	18 128	15 777	28 508
4	17 924	15 749	29 148
5	17 300	15 024	28 012

场景	日碳排放总量
场景	模式1	模式2	模式3
1	13 271	11 662	26 746
2	13 065	11 816	26 002
3	13 587	12 000	26 048
4	13 432	11 846	26 712
5	12 680	11 123	26 598

历史数据驱动的综合能源系统分布式鲁棒低碳优化模型

Distributed robust low-carbon optimization model for integrated energy systems driven by historical data

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 27

相关文章 15

编辑推荐

Metrics

本文评价

设备	容量/kW	容量下限/%	容量上限/%	爬坡约束/%
储电	450	10	90	20
储热	500	10	90	20
储气	150	10	90	20
储氢	200	10	90	20

∞-范数的置信度	日调度成本
∞-范数的置信度	1-范数	混合范数
0.50	16 689	16 125
0.60	16 689	16 357
0.70	16 689	16 453
0.80	16 689	16 523
0.99	16 689	16 589

1-范数的置信度	日调度成本
1-范数的置信度	∞-范数	混合范数
0.50	16 643	16 223
0.60	16 643	16 311
0.70	16 643	16 358
0.80	16 643	16 412
0.99	16 643	16 630

[1]	丁新宇, 周庆才, 迟耀丹, 张尧, 王俊喜, 王超, 贾红丹, 林国雄. 新型电力系统建模、控制与源荷预测研究进展[J]. 综合智慧能源, 2026, 48(3): 1-14.
[2]	陈锋, 路小敏, 李梦杨, 张涛, 杨帆. 基于多智能体强化学习的多能互补能源系统优化运行[J]. 综合智慧能源, 2026, 48(3): 15-26.
[3]	穆雨彤, 王巍. 基于APO-PSO的风光火储联合发电系统低碳优化调度[J]. 综合智慧能源, 2026, 48(3): 37-46.
[4]	张杨, 陶生虎, 刘琪. 考虑农村用能多样性的碳路径分析及综合能量管理策略研究[J]. 综合智慧能源, 2026, 48(3): 56-64.
[5]	徐聪, 徐静静, 江婷, 薛东, 闫立辰. 数据驱动的综合能源系统运行优化研究[J]. 综合智慧能源, 2026, 48(1): 34-42.
[6]	潘雷, 丁云飞, 庞毅, 王宇璇, 陈建伟, 高瑞, 张立阳. 基于SC-SAC算法的REHMIS-IES优化调度策略[J]. 综合智慧能源, 2026, 48(1): 43-58.
[7]	薛东, 徐静静, 江婷, 王晓海, 徐聪. 基于双重特征处理的园区综合能源系统供热负荷预测研究[J]. 综合智慧能源, 2026, 48(1): 59-66.
[8]	窦翔, 李卓群, 张哲, 温鑫, 赵勃, 韩燕, 仲声. 基于CNN-BiLSTM-RF-KDE的综合能源系统负荷预测[J]. 综合智慧能源, 2025, 47(9): 60-70.
[9]	谭甲群, 吕如轩, 鞠洪晋, 洪春雪, 肖海平, 雷兢, 韩振兴. 基于改进秃鹰搜索算法的风光火储综合能源系统优化调度策略研究[J]. 综合智慧能源, 2025, 47(8): 68-76.
[10]	宋坤, 顾文波. 考虑不确定性的综合能源系统建模及优化研究进展[J]. 综合智慧能源, 2025, 47(7): 32-43.
[11]	陈亮, 刘桂英, 粟时平, 唐长久, 王辰浩, 郭思桐. 基于双层网络PER-MADDPG算法的综合能源系统协调优化调度[J]. 综合智慧能源, 2025, 47(7): 44-54.
[12]	邢作霞, 赵子逸, 孙浩, 张鹏飞, 付启桐. 基于电制氢多级利用的综合能源系统低碳经济运行优化研究[J]. 综合智慧能源, 2025, 47(7): 71-81.
[13]	张德斌, 林文野, 何梓轩, 岳心如, 宋文吉, 冯自平, FARID Mohammed Mehdi, USHAK DE GRAGEDA Svetlana Nikolaevna. 计及广义储能的建筑产消者社区综合能源系统日前调度优化[J]. 综合智慧能源, 2025, 47(7): 82-92.
[14]	湛国华, 张先勇, 魏圣莹, 张孝顺, 李丽. 基于T-Graphormer的电网碳排放因子预测方法[J]. 综合智慧能源, 2025, 47(6): 30-36.
[15]	李晓宁, 孙娜, 黄阿敏, 董海鹰. 基于蛇优化算法的PEMFC空气供给系统模糊自抗扰控制[J]. 综合智慧能源, 2025, 47(6): 57-73.