Optimization of Low-Carbon Operation for Multi-Energy Microgrids Considering Indirect Carbon Emissions from Electricity Trading

YI Tao, LIANG Xiang, LIU Yuan

Electric Power Construction ›› 2026, Vol. 47 ›› Issue (11) : 148-159.

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Electric Power Construction ›› 2026, Vol. 47 ›› Issue (11) : 148-159. DOI: 10.12204/j.issn.1000-7229.2026.11.011
Power Economics

Optimization of Low-Carbon Operation for Multi-Energy Microgrids Considering Indirect Carbon Emissions from Electricity Trading

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Abstract

[Objective] To accurately reflect the carbon emission differences on the load side, fully account for the total carbon emissions generated during system operation, and explore the potential of low-carbon demand response, a low-carbon operation optimization model for multi-energy microgrids considering indirect carbon emissions from electricity transactions is proposed. [Methods] First, an operation optimization model of multi-energy microgrids was established based on the energy flow constraints of electricity, heat and gas, as well as the complementary demand response characteristics of multi-energy carriers. To precisely differentiate carbon accounting responsibilities among load-side entities, indirect carbon emissions from purchased electricity were quantified according to power transaction paths, and the source and path allocation of purchased power were incorporated into optimization decisions. Furthermore, a low-carbon operation optimization model for multi-energy microgrids integrating demand response was developed. The model was formulated in the MATLAB environment using the YALMIP toolbox and solved by the CPLEX solver. [Results] Compared with the conventional demand response scheme without indirect carbon emission costs, the daily system operation cost decreases by 3.90%, and the total system carbon emissions drop by 552.63 kg, representing a reduction of 50.84%. In contrast to the regional average carbon emission factor method, the indirect carbon emissions of the system under the power transaction contract path are reduced by 547.46 kg, achieving a decline of 44.23%. [Conclusions] The proposed method provides theoretical and model references for the economical and low-carbon operation of multi-energy microgrids, and effectively stimulates the enthusiasm of end-users for low-carbon response.

Key words

microgrid systems / electricity transaction / indirect carbon emissions / low-carbon operation

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YI Tao , LIANG Xiang , LIU Yuan. Optimization of Low-Carbon Operation for Multi-Energy Microgrids Considering Indirect Carbon Emissions from Electricity Trading[J]. Electric Power Construction. 2026, 47(11): 148-159 https://doi.org/10.12204/j.issn.1000-7229.2026.11.011

References

[1]
El Hassani S, Oueslati F, Horma O, et al. Techno-economic feasibility and performance analysis of an islanded hybrid renewable energy system with hydrogen storage in Morocco[J]. Journal of Energy Storage, 2023, 68: 107853.
[2]
王常乐, 刘海涛, 吕志鹏. 基于灰狼算法的直流微电网H∞鲁棒控制[J]. 供用电, 2024, 41(4): 53-61.
Wang Changle, Liu Haitao, Lü Zhipeng. H∞robust control of DC microgrid based on grey wolf algorithm[J]. Distribution & Utilization, 2024, 41(4): 53-61.
[3]
Khan K, Su C W, Khurshid A, et al. Does energy security improve renewable energy: a geopolitical perspective[J]. Energy, 2023, 282: 128824.
[4]
樊会丛, 段志国, 陈志永, 等. 基于多智能体深度策略梯度的离网型微电网双层优化调度[J]. 中国电力, 2025, 58(5): 11-20, 32.
Fan Huicong, Duan Zhiguo, Chen Zhiyong, et al. Two-layer optimization scheduling for off-grid microgrids based on multi-agent deep policy gradient[J]. Electric Power, 2025, 58(5): 11-20, 32.
[5]
申珂光, 刘东, 翁嘉明, 等. 交直流混合微电网配微协同典型应用场景与测试算例[J]. 供用电, 2025, 42(10):71-79.
Shen Keguang, Liu Dong, Weng Jiaming, et al. Typical application scenarios and test cases of distribution-microgrid coordination for AC/DC hybrid microgrid[J]. Distribution & Utilization, 2025, 42(10):71-79.
[6]
周煜韬, 王洪达, 焦志鹏, 等. 微电网效能评价指标体系与评价方法研究综述[J]. 广东电力, 2025, 38(8): 63-79.
Zhou Yutao, Wang Hongda, Jiao Zhipeng, et al. Review of microgrid efficiency evaluation index systems and methods[J]. Guangdong Electric Power, 2025, 38(8): 63-79.
[7]
Luo L, Abdulkareem S S, Rezvani A, et al. Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty[J]. Journal of Energy Storage, 2020, 28: 101306.
[8]
Xie X H, Yang H J, Wang B, et al. Optimal day-ahead scheduling strategy of microgrid considering regional pollution and potential load curtailment[J]. Global Energy Interconnection, 2024, 7(6): 749-760.
[9]
钟锦星, 陈艺丹, 叶羽转, 等. 考虑源荷时序关联特性与需求响应弹性调节的园区低碳规划方法[J]. 广东电力, 2025, 38(9): 93-107.
Zhong Jinxing, Chen Yidan, Ye Yuzhuan, et al. Low-carbon park planning method considering source-load time-series correlation and demand response elasticity adjustment[J]. Guangdong Electric Power, 2025, 38(9): 93-107.
[10]
郭鑫, 张俊拓, 崇玉婷, 等. 基于多任务进化混沌粒子群的光储直柔微电网协同优化方法[J/OL]. 控制与决策,2026-03-27.https://doi.org/10.13195/j.kzyjc.2025.1102.
Guo Xin, Zhang Juntuo, Chong Yuting, et al. A collaborative optimization approach for microgrids integrating photovoltaics, energy storage, direct current and flexibility using multi-task evolutionary chaotic particle swarm optimization[J/OL]. Control and Decision, 2026-03-27.https://doi.org/10.13195/j.kzyjc.2025.1102.
[11]
Vankudoth L, Badar A Q H. Development and analysis of scheduling strategies for utilizing shared energy storage system in networked microgrids[J]. Journal of Energy Storage, 2024, 97: 112691.
[12]
张珍凤, 贺慧. 多能互补微电网系统的能量优化配置分析[J]. 电子技术, 2025, 54(11): 202-203.
Zhang Zhenfeng, He Hui. Analysis of energy optimization configuration of multi-energy complementary microgrid system[J]. Electronic Technology, 2025, 54(11): 202-203.
[13]
李佳玮, 孙庆贺, 王琼, 等. 计及不确定相关性的多能微电网数据驱动分布鲁棒优化调度[J]. 电力建设, 2025, 46(8): 22-33.
Li Jiawei, Sun Qinghe, Wang Qiong, et al. Multi-energy microgrid data-driven distributionally robust optimization dispatch considering uncertainty correlation[J]. Electric Power Construction, 2025, 46(8): 22-33.
[14]
李鸿, 朱继忠, 董瀚江. 考虑协变量因素的多能微电网两阶段分布鲁棒优化调度[J]. 中国电机工程学报, 2025, 45(3): 822-834.
Li Hong, Zhu Jizhong, Dong Hanjiang. Two-stage distributionally robust optimization scheduling for multi-energy microgrid considering covariate factors[J]. Proceedings of the CSEE, 2025, 45(3): 822-834.
[15]
Li R H, Zhou J, Qiu Z T, et al. Bi-level optimization of hybrid energy conversion system based on a multi-distinct low-carbon microgrid[J]. Renewable Energy, 2025, 239: 122095.
[16]
金鑫, 李超, 潘廷哲, 等. 基于改进碳交易机制的综合能源系统低碳需求响应优化方法[J]. 电力科学与技术学报, 2025, 40(6): 221-232.
Jin Xin, Li Chao, Pan Tingzhe, et al. Low-carbon demand response optimization method for integrated energy system based on improved carbon trading mechanism[J]. Journal of Electric Power Science and Technology, 2025, 40(6): 221-232.
[17]
张海峰, 李晓华, 周兴华. 考虑需求响应与碳交易的综合能源系统优化调度策略[J]. 电力科学与技术学报, 2025, 40(5): 218-226.
Zhang Haifeng, Li Xiaohua, Zhou Xinghua. Optimization scheduling strategy of integrated energy system considering demand response and carbon trading[J]. Journal of Electric Power Science and Technology, 2025, 40(5): 218-226.
[18]
贺代文, 张新, 姜金朋, 等. 计及源-荷灵活响应和新型降碳机制的孤岛综合能源系统优化调度[J]. 高压电器, 2025, 61(5): 20-30.
He Daiwen, Zhang Xin, Jiang Jinpeng, et al. Optimal scheduling of island integrated energy system considering flexible response from source side to load side and new carbon reduction mechanism[J]. High Voltage Apparatus, 2025, 61(5): 20-30.
[19]
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.
[20]
蒋丽, 韩冬. 基于TD3算法的配-微电网异构智能体主从博弈分层低碳优化运行策略[J/OL]. 电力系统及其自动化学报,2026-03-06.https://doi.org/10.19635/j.cnki.csu-epsa.001811.
Jiang Li, Han Dong. Hierarchical low-carbon optimal operation strategy based on TD3 algorithm for Stackelberg game of heterogeneous agents in distribution-microgrid[J/OL]. Proceedings of the CSU-EPSA, 2026-03-06.https://doi.org/10.19635/j.cnki.csu-epsa.001811.
[21]
杨丰任, 王鸿, 王致杰. 基于碳排放生产优先级的综合能源虚拟电厂优化运行策略[J]. 电力科学与技术学报, 2024, 39(5): 192-202.
Yang Fengren, Wang Hong, Wang Zhijie. Optimal operation strategy of integrated energy virtual power plant based on production priority of carbon emission[J]. Journal of Electric Power Science and Technology, 2024, 39(5): 192-202.
[22]
李振坤, 李逸沐, 罗潇, 等. 计及碳交易和绿电占比的园区微电网优化运行[J]. 电测与仪表, 2025, 62(5): 130-139.
Li Zhenkun, Li Yimu, Luo Xiao, et al. Optimal operation of microgrid in the park considering carbon trading and the proportion of green electricity[J]. Electrical Measurement & Instrumentation, 2025, 62(5): 130-139.
[23]
李怡晨, 李强, 李宏伟, 等. 融合阶梯式碳交易与需求响应的源荷协同优化[J]. 广东电力, 2024, 37(4): 71-79.
Li Yichen, Li Qiang, Li Hongwei, et al. Source-load collaborative optimization combining stepwise carbon trading and demand response[J]. Guangdong Electric Power, 2024, 37(4): 71-79.
[24]
路博凯, 吕干云, 刘奕辰, 等. 计及CCER阶梯式碳交易与综合需求响应的微网优化调度[J]. 电气自动化, 2026, 48(1): 59-62, 66.
Lu Bokai, Lyu Ganyun, Liu Yichen, et al. Microgrid optimization scheduling considering CCER tiered carbon trading and comprehensive demand response[J]. Electrical Automation, 2026, 48(1): 59-62, 66.
[25]
Understanding electricity scope 2 attribution rules[EB/OL].(2022-11-16)[2023-08-31]. https://www.electricitymaps.com/guides/accounting-guide.
[26]
周天睿, 康重庆, 徐乾耀, 等. 电力系统碳排放流的计算方法初探[J]. 电力系统自动化, 2012, 36(11): 44-49.
Zhou Tianrui, Kang Chongqing, Xu Qianyao, et al. Preliminary investigation on a method for carbon emission flow calculation of power system[J]. Automation of Electric Power Systems, 2012, 36(11): 44-49.
[27]
汪超群, 陈懿, 文福拴, 等. 电力系统碳排放流理论改进与完善[J]. 电网技术, 2022, 46(5): 1683-1693.
Wang Chaoqun, Chen Yi, Wen Fushuan, et al. Improvement and perfection of carbon emission flow theory in power systems[J]. Power System Technology, 2022, 46(5): 1683-1693.
[28]
刘天蔚, 边晓燕, 吴珊, 等. 电力系统碳排放核算综述与展望[J]. 电力系统保护与控制, 2024, 52(4): 176-187.
Liu Tianwei, Bian Xiaoyan, Wu Shan, et al. Overview and prospect of carbon emission accounting in electric power systems[J]. Power System Protection and Control, 2024, 52(4): 176-187.
[29]
李姚旺, 刘昱良, 杨晓斌, 等. 计及电量交易信息的用电碳计量方法[J]. 中国电机工程学报, 2024, 44(2): 439-450.
Li Yaowang, Liu Yuliang, Yang Xiaobin, et al. Electricity carbon metering method considering ElectricityElectricity carbon metering method considering electricity transaction information transaction information[J]. Proceedings of the CSEE, 2024, 44(2): 439-450.
[30]
杨维, 张宁, 康重庆. 基于电力市场合约的企业电力碳排放核算研究[J]. 电网技术, 2024, 48(10): 4115-4124.
Yang Wei, Zhang Ning, Kang Chongqing. Research on accounting for enterprise electricity carbon emissions based on electricity market contracts[J]. Power System Technology, 2024, 48(10): 4115-4124.
[31]
张显, 谢开, 张晓静, 等. 基于合约路径的电力用户分时碳排放溯源[J]. 电力系统自动化, 2026, 50(4): 56-68.
Zhang Xian, Xie Kai, Zhang Xiaojing, et al. Time-of-use traceback of carbon emissions for electricity consumers based on contract paths[J]. Automation of Electric Power Systems, 2026, 50(4): 56-68.
[32]
左超文. 基于动态分时电价策略的微电网分层优化调度[D]. 贵阳: 贵州大学, 2024.
Zuo Chaowen. Hierarchical optimization scheduling of microgrids based on dynamic time-of-use pricing strategies[D]. Guiyang: Guizhou University, 2024.
[33]
蔡瑶. 交直流混合多能微网优化调度研究[D]. 秦皇岛: 燕山大学, 2023.
Cai Yao. Research on optimal scheduling of hybrid AC/DC multi-energy microgrid[D]. Qinhuangdao: Yanshan University, 2023.
[34]
迟一璇. 考虑源-荷协同的综合能源系统低碳经济优化研究[D]. 阜新: 辽宁工程技术大学, 2024.
Chi Yixuan. Research on low-carbon economy optimization of integrated energy system considering source-load synergy[D]. Fuxin: Liaoning Technical University, 2024.
[35]
蔡瑶, 卢志刚, 潘尧, 等. 计及多重差异的交直流混合多能微网多时间尺度优化调度[J]. 电工技术学报, 2024, 39(11): 3392-3410.
Cai Yao, Lu Zhigang, Pan Yao, et al. Multi-time-scale optimal scheduling of AC-DC hybrid multi-energy microgrid considering multiple differences[J]. Transactions of China Electrotechnical Society, 2024, 39(11): 3392-3410.
[36]
高聪冲. 基于博弈论的区域综合能源型多微网优化运行研究[D]. 西安: 西安理工大学, 2024.
Gao Congchong. Research on optimal operation of regional comprehensive energy-based multi-microgrid based on game theory[D]. Xi'an: Xi'an University of Technology, 2024.
[37]
滕越. 计及P2G平抑波动能力的综合能源系统运行优化研究[D]. 北京: 华北电力大学, 2024.
Teng Yue. Optimization study of integrated energy system operation considering P2G fluctuation smoothing capability[D]. Beijing: North China Electric Power University, 2024.
[38]
任伟嘉. 计及供需双响应的IES低碳经济调度及效益评价研究[D]. 北京: 华北电力大学, 2024.
Ren Weijia. Study on IES low carbon economic dispatch considering dual response of supply and demand and benefit evaluation[D]. Beijing: North China Electric Power University, 2024.
[39]
魏震波, 马新如, 郭毅, 等. 碳交易机制下考虑需求响应的综合能源系统优化运行[J]. 电力建设, 2022, 43(1): 1-9.
Abstract
综合能源系统是实现“双碳”目标的有效途径,为进一步挖掘其需求侧可调节潜力对碳减排的作用,提出了一种碳交易机制下考虑需求响应的综合能源系统优化运行模型。首先,根据负荷响应特性将需求响应分为价格型和替代型2类,分别建立了基于价格弹性矩阵的价格型需求响应模型,及考虑用能侧电能和热能相互转换的替代型需求响应模型;其次,采用基准线法为系统无偿分配碳排放配额,并考虑燃气轮机和燃气锅炉的实际碳排放量,构建一种面向综合能源系统的碳交易机制;最后,以购能成本、碳交易成本及运维成本之和最小为目标函数,建立综合能源系统低碳优化运行模型,并通过4类典型场景对所提模型的有效性进行了验证。通过对需求响应灵敏度、燃气轮机热分配比例和不同碳交易价格下系统的运行状态分析发现,合理分配价格型和替代型需求响应及燃气轮机产热比例有利于提高系统运行经济性,制定合理的碳交易价格可以实现系统经济性和低碳性协同。
Wei Zhenbo, Ma Xinru, Guo Yi, et al. Optimized operation of integrated energy system considering demand response under carbon trading mechanism[J]. Electric Power Construction, 2022, 43(1): 1-9.

The integrated energy system (IES) is an effective way to achieve the“carbon neutrality and emission peak”goal. In order to further explore the role of the adjustable potential of demand side on carbon emission reduction, an optimized operation model of IES considering the demand response under the carbon trading mechanism is proposed. Firstly, according to the characteristics of load response, the demand response is divided into two types: price-type and substitution-type. The price-type demand response model is established on the basis of price elasticity matrix, and the substitution-type demand response model is constructed by considering the conversion of electricity and heat. Secondly, base-line method is used to allocate free carbon emission quota for the system, and considering the actual carbon emissions of gas turbine and gas boiler, a carbon trading mechanism for the IES is constructed. Finally, a low-carbon optimal operation model of IES is established, whose objective is to minimize the sum cost of energy purchase, cost of carbon transaction and cost of IES operation and maintenance. The effectiveness of the proposed model is verified through four typical scenarios. By analyzing the sensitivity of demand response, heat distribution ratio of gas turbine and the operating state of the system under different carbon trading prices, it is found that reasonable allocation of price-type and substitution-type demand response and heat production ratio of gas turbine is beneficial to improve the operating economy of the system. Making reasonable carbon trading price can realize the coordination of system economy and low carbon.

Footnotes

利益冲突声明(Conflict of Interests): 所有作者声明不存在利益冲突。

作者贡献声明(Authors' Contributions): 易涛承担研究方向确定、论文框架设计、论文模型构建、论文修订与审核工作;梁湘承担算例分析、图表绘制、论文撰写工作;刘源承担可行性调查分析、论文修订工作。所有作者均阅读并同意了论文终稿内容。

Funding

National Natural Science Foundation of China for Young Scientists(72204086)
Fundamental Research Funds for the Central Universities(2026MS044)
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