考虑需求响应和碳排放的热电联供型微电网优化调度

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1348 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract To address issues such as high carbon emissions and insufficient renewable energy utilization in multi-energy complementary microgrid involving carbon capture and power-to-gas combined heat and power (CHP) units, this paper constructs a joint scheduling model that integrates system economic and low-carbon operation, based on modeling the uncertainty, correlation, and randomness of wind and photovoltaic power generation outputs. The model uses the total operational economic benefits of the system with carbon trading costs as the objective function, and incorporates constraints such as power balance considering demand response on the user side and thermal-electric characteristics. By optimizing load-side demand and unit outputs, the model enhances system flexibility, improves renewable energy accommodation capacity, and reduces carbon emissions and operational costs. Experimental results demonstrate that compared to other optimization scheduling methods, the proposed approach reduces carbon dioxide emissions and operational costs by 1.8% and 3.0%, respectively.

Key words： combined heat and power (CHP) units multi-energy complementary systems micro-grids demand response

Received: 08 December 2025

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WU Jianyu
	CHAI Qinqin
	LI Jiabao
	LAI Qianling

Cite this article:

WU Jianyu,CHAI Qinqin,LI Jiabao等. Optimal dispatch of cogeneration-based microgrids considering demand response and carbon emissions[J]. Electrical Engineering, 2026, 27(9): 11-20.

URL:

https://dqjs.cesmedia.cn/EN/Y2026/V27/I9/11

[1] 李思颖, 易俊, 林伟芳. 考虑碳捕集技术的热电联供型微电网低碳运行研究[J]. 武汉大学学报(工学版), 2023, 56(11): 1358-1367.
[2] 黄治军. 多种可再生能源渗透场景下的热电联产系统优化[J]. 热能动力工程, 2023, 38(4): 121-130.
[3] 李玉婷, 彭敏放. 考虑碳捕集与甲烷化的综合能源微网分布式优化调度[J]. 电力自动化设备, 2023, 43(3): 46-53.
[4] Clegg S, Mancarella P.Integrated electrical and gas network flexibility assessment in low-carbon multi- energy systems[J]. IEEE Transactions on Sustainable Energy, 2016, 7(2): 718-731.
[5] Khani H, Farag H E Z. Optimal day-ahead scheduling of power-to-gas energy storage and gas load mana- gement in wholesale electricity and gas markets[J]. IEEE Transactions on Sustainable Energy, 2018, 9(2): 940-951.
[6] Cheng Ying, Liu Mingbo, Chen Honglin, et al.Optimization of multi-carrier energy system based on new operation mechanism modelling of power-to-gas integrated with CO₂-based electrothermal energy storage[J]. Energy, 2021, 216: 119269.
[7] 韩丽, 王冲, 于晓娇, 等. 考虑风电爬坡灵活调节的碳捕集电厂低碳经济调度[J]. 电工技术学报, 2024, 39(7): 2033-2045.
[8] 董雷, 杨子民, 乔骥, 等. 基于分层约束强化学习的综合能源多微网系统优化调度[J]. 电工技术学报, 2024, 39(5): 1436-1453.
[9] 袁坤龙, 张少康, 常冉, 等. 阶梯式碳交易机制下计及电-气-热综合能源系统需求响应优化运行[J]. 电气技术, 2024, 25(1): 8-16.
[10] 孙海翠. 一种基于光伏-光热-储能联合发电的能源基地功率协调控制方案[J]. 电气技术, 2024, 25(11): 22-29.
[11] Chen Jiajia, Qi B X, Rong Z K, et al.Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement[J]. Energy, 2021, 217: 119387.
[12] Xu Xiandong, Zhou Yue, Qadrdan M, et al.Unlocking the flexibility of CHP in district heating systems to provide frequency response[C]//2019 IEEE Milan PowerTech, Milan, Italy, 2019:1-6.
[13] Ni Linna, Liu Weijia, Wen Fushuan, et al.Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diver- sified storage devices[J]. Journal of Modern Power Systems and Clean Energy, 2018, 6(3): 423-437.
[14] Ma Yiming, Wang Haixin, Hong Feng, et al.Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system[J]. Energy, 2021, 236: 121392.
[15] 黄大为, 郭念康, 于娜, 等. 面向系统灵活性提升的大用户激励型需求响应优化策略[J]. 电工技术学报, 2024, 39(21): 6778-6792.
[16] 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.
[17] 杨海柱, 李梦龙, 江昭阳, 等. 考虑需求侧电热气负荷响应的区域综合能源系统优化运行[J]. 电力系统保护与控制, 2020, 48(10): 30-37.
[18] 韩丽, 陈硕, 王施琪, 等. 考虑风光消纳与电动汽车灵活性的调度策略[J]. 电工技术学报, 2024, 39(21): 6793-6803.
[19] 季克勤, 卢昊威. 考虑多元灵活性资源的配电网协同优化调度[J]. 电气技术, 2024, 25(7): 23-31.
[20] Chen Zexing, Zhang Yongjun, Ji Tianyao, et al.Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded[J]. Journal of Modern Power Systems and Clean Energy, 2018, 6(3): 495-508.
[21] 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.
[22] Yang Jingwei, Zhang Ning, Cheng Yaohua, et al.Modeling the operation mechanism of combined P2G and gas-fired plant with CO₂ recycling[J]. IEEE Transactions on Smart Grid, 2019, 10(1): 1111-1121.
[23] Cheng Yaohua, Zhang Ning, Wang Yi, et al.Modeling carbon emission flow in multiple energy systems[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 3562-3574.
[24] 陈志, 胡志坚, 翁菖宏, 等. 基于阶梯碳交易机制的园区综合能源系统多阶段规划[J]. 电力自动化设备, 2021, 41(9): 148-155.
[25] Li Fangyuan, Qin Jiahu, Kang Yu.Closed-loop hierarchical operation for optimal unit commitment and dispatch in microgrids: a hybrid system app- roach[J]. IEEE Transactions on Power Systems, 2020, 35(1): 516-526.
[26] Jin Shunping, Wang Shoupeng, Fang Fang.Game theoretical analysis on capacity configuration for microgrid based on multi-agent system[J]. Inter- national Journal of Electrical Power & Energy Systems, 2021, 125: 106485.
[27] Li Weidong, Li Tie, Wang Haixin, et al.Optimal dispatch model considering environmental cost based on combined heat and power with thermal energy storage and demand response[J]. Energies, 2019, 12(5): 817.
[28] Peng Daoxin, Wu Hongliang, Wang Ling.Com- prehensive energy cooperative optimization model based on energy conversion efficiency considering investment benefit[J]. International Journal of Energy Research, 2021, 45(2): 2997-3015.
[29] 安源, 嘉程昊, 宁旭阳, 等. 考虑风光相关性与灵活碳捕集的互补系统低碳经济调度[J]. 太阳能学报, 2024, 45(11): 40-49.
[30] Wang Haixin, Yang Junyou, Chen Zhe, et al.Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks[J]. Applied Energy, 2020, 267: 114879.