IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i18p4705-d1482564.html
   My bibliography  Save this article

Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas

Author

Listed:
  • Lihui Gao

    (School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

  • Shuanghao Yang

    (School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

  • Nan Chen

    (School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

  • Junheng Gao

    (School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

Abstract

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system’s carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system.

Suggested Citation

  • Lihui Gao & Shuanghao Yang & Nan Chen & Junheng Gao, 2024. "Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas," Energies, MDPI, vol. 17(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4705-:d:1482564
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/18/4705/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/18/4705/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harsh, Pratik & Das, Debapriya, 2022. "Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    2. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    3. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chengcheng Ma & Zhijian Hu, 2025. "Low-Carbon Economic Scheduling of Integrated Energy System Considering Flexible Supply–Demand Response and Diversified Utilization of Hydrogen," Sustainability, MDPI, vol. 17(4), pages 1-23, February.
    2. Xunwen Zhao & Hailin Mu & Nan Li & Xue Kong & Xunpeng Shi, 2025. "Optimization Research on a Novel Community Integrated Energy System Based on Solar Energy Utilization and Energy Storage," Energies, MDPI, vol. 18(5), pages 1-19, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    2. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
    3. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    4. Wang, Yi & Qiu, Dawei & Sun, Mingyang & Strbac, Goran & Gao, Zhiwei, 2023. "Secure energy management of multi-energy microgrid: A physical-informed safe reinforcement learning approach," Applied Energy, Elsevier, vol. 335(C).
    5. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    6. Tie, Yingqi & Hu, Bo & Shao, Changzheng & Huang, Wei & Qi, Feng & Xie, Kaigui, 2023. "Integrated flexibility characterization and measurement of distributed multi-energy systems considering temporal coupling constraints," Energy, Elsevier, vol. 283(C).
    7. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
    8. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Yan, Yichuan & Tian, Ning, 2023. "Natural gas demand response strategy considering user satisfaction and load volatility under dynamic pricing," Energy, Elsevier, vol. 277(C).
    9. Zejun Tong & Chun Zhang & Xiaotai Wu & Pengcheng Gao & Shuang Wu & Haoyu Li, 2023. "Economic Optimization Control Method of Grid-Connected Microgrid Based on Improved Pinning Consensus," Energies, MDPI, vol. 16(3), pages 1-31, January.
    10. Siwen Wang & Hui Chen & Chunyang Gong & Yanfei Shang & Zhixin Wang, 2024. "The Operation Strategy of a Multi-Microgrid Considering the Interaction of Different Subjects’ Interests," Energies, MDPI, vol. 17(19), pages 1-20, September.
    11. Xu, Qingyang & Sun, Feihu & Cai, Qiran & Liu, Li-Jing & Zhang, Kun & Liang, Qiao-Mei, 2022. "Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China," Renewable Energy, Elsevier, vol. 190(C), pages 945-958.
    12. Sivaneasan, Balakrishnan & Kandasamy, Nandha Kumar & Lim, May Lin & Goh, Kwang Ping, 2018. "A new demand response algorithm for solar PV intermittency management," Applied Energy, Elsevier, vol. 218(C), pages 36-45.
    13. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    14. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    15. Ramos-Teodoro, Jerónimo & Rodríguez, Francisco & Berenguel, Manuel & Torres, José Luis, 2018. "Heterogeneous resource management in energy hubs with self-consumption: Contributions and application example," Applied Energy, Elsevier, vol. 229(C), pages 537-550.
    16. Lu, Qing & Lü, Shuaikang & Leng, Yajun, 2019. "A Nash-Stackelberg game approach in regional energy market considering users’ integrated demand response," Energy, Elsevier, vol. 175(C), pages 456-470.
    17. Kocaman, Ayse Selin & Ozyoruk, Emin & Taneja, Shantanu & Modi, Vijay, 2020. "A stochastic framework to evaluate the impact of agricultural load flexibility on the sizing of renewable energy systems," Renewable Energy, Elsevier, vol. 152(C), pages 1067-1078.
    18. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    19. Zezhong Li & Xiangang Peng & Yilin Xu & Fucheng Zhong & Sheng Ouyang & Kaiguo Xuan, 2023. "A Stackelberg Game-Based Model of Distribution Network-Distributed Energy Storage Systems Considering Demand Response," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
    20. Yao, Wenliang & Wang, Chengfu & Yang, Ming & Wang, Kang & Dong, Xiaoming & Zhang, Zhenwei, 2023. "A tri-layer decision-making framework for IES considering the interaction of integrated demand response and multi-energy market clearing," Applied Energy, Elsevier, vol. 342(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4705-:d:1482564. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.