The Optimal Scheduling of Integrated Energy System Considering the Incentive and Punishment Mechanism of Electric and Thermal Carbon Emission Factors

被引:0
作者
Wang, Kaiyan [1 ]
He, Hengxiang [1 ]
Yang, Ningning [1 ]
Wang, Xiaowei [1 ]
Jia, Rong [1 ]
机构
[1] Xian Univ Technol, Sch Elect Engn, Xian 710048, Peoples R China
来源
IEEE ACCESS | 2025年 / 13卷
基金
中国国家自然科学基金;
关键词
Carbon dioxide; Optimal scheduling; Thermal energy; Electricity; Mathematical models; Load modeling; Demand response; Resistance heating; Job shop scheduling; Hydrogen; Integrated energy systems; thermal energy cascade utilization; dynamic electricity and thermal carbon emission factors; integrated demand response;
D O I
10.1109/ACCESS.2025.3542018
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the context of global industrialization, integrated energy systems (IES) have emerged as a crucial means of facilitating green and low-carbon transformation. To comprehensively explore the potential for carbon reduction through source-load synergy and achieve low-carbon and high-efficiency operation of the system, an IES optimal scheduling method that incorporates a reward and punishment mechanism for dynamic electricity and thermal carbon emission factors is proposed. Firstly, the concepts of energy coupling and thermal energy cascade utilization are considered, and an IES-coupled equipment cascade utilization model with carbon capture is established with the objective of realizing high-grade use of thermal energy in combination with thermal load demand. Secondly, an improved IES dynamic electricity and thermal carbon emission factors model is proposed to characterize the carbon emission intensity and renewable energy consumption capacity. Based on this, an integrated demand response (IDR) mechanism driven by electricity, thermal reward, and carbon price is established to guide users toward low-carbon behaviors and renewable energy consumption. Finally, a two-stage optimal scheduling model is constructed. In the pre-scheduling phase, the initial scheduling plan is solved, and the load distribution is adjusted by the integrated demand response. In the re-scheduling phase, the load curve is updated to obtain the final scheduling plan. Through simulation verification, the proposed scheduling model reduces carbon emissions by 7.7 %, improves the renewable energy consumption rate by 4 %, and reduces the comprehensive operating cost of the system by 4.3 %, which indicates that the method proposed in this paper can effectively promote the emission reduction and consumption and reduce the operating cost of the system.
引用
收藏
页码:30874 / 30893
页数:20
相关论文
共 34 条
[1]   Low-carbon operation method of the building based on dynamic carbon emission factor of power system [J].
Bu, Le ;
Chen, Xingying ;
Gan, Lei ;
Yu, Kun ;
Zhou, Yue ;
Cao, Jiawei ;
Cao, Yuan .
IET SMART GRID, 2023, 6 (01) :67-85
[2]   Thermodynamic analysis of a hybrid energy system coupling solar organic Rankine cycle and ground source heat pump: Exploring heat cascade utilization [J].
Chen, Liangqi ;
Yue, Huifeng ;
Wang, Jiangfeng ;
Lou, Juwei ;
Wang, Shunsen ;
Guo, Yumin ;
Deng, Bohao ;
Sun, Lu .
ENERGY, 2023, 284
[3]   An optimization on an integrated energy system of combined heat and power, carbon capture system and power to gas by considering flexible load [J].
Chen, Maozhi ;
Lu, Hao ;
Chang, Xiqiang ;
Liao, Haiyan .
ENERGY, 2023, 273
[4]  
Cheng Y. B., 2024, P CSEE, V44
[5]   Low-Carbon Operation of Multiple Energy Systems Based on Energy-Carbon Integrated Prices [J].
Cheng, Yaohua ;
Zhang, Ning ;
Zhang, Baosen ;
Kang, Chongqing ;
Xi, Weimin ;
Feng, Mengshuang .
IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (02) :1307-1318
[6]   Low carbon and economic optimal operation of electricity-gas integrated energy system considering demand response [J].
Duan, Jiandong ;
Xia, Yerui ;
Cheng, Ran ;
Gao, Qi ;
Liu, Fan .
SUSTAINABLE ENERGY GRIDS & NETWORKS, 2024, 38
[7]   Variation-based complementarity assessment between wind and solar resources in China [J].
Guo, Yi ;
Ming, Bo ;
Huang, Qiang ;
Yang, Ziwei ;
Kong, Yun ;
Wang, Xianxun .
ENERGY CONVERSION AND MANAGEMENT, 2023, 278
[8]   Assessing economic and environmental performance of multi-energy sharing communities considering different carbon emission responsibilities under carbon tax policy [J].
Li, Longxi ;
Zhang, Sen ;
Cao, Xilin ;
Zhang, Yuqing .
JOURNAL OF CLEANER PRODUCTION, 2021, 328
[9]   Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation [J].
Liu, Tianhao ;
Tian, Jun ;
Zhu, Hongyu ;
Goh, Hui Hwang ;
Liu, Hui ;
Wu, Thomas ;
Zhang, Dongdong .
ENERGY, 2023, 277
[10]   Techno-economic analysis on CO2 mitigation by integrated carbon capture and methanation [J].
Lv, Zongze ;
Du, Hong ;
Xu, Shaojun ;
Deng, Tao ;
Ruan, Jiaqi ;
Qin, Changlei .
APPLIED ENERGY, 2024, 355