IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9764-d883002.html
   My bibliography  Save this article

Optimal Scheduling of Thermoelectric Coupling Energy System Considering Thermal Characteristics of DHN

Author

Listed:
  • Guangdi Li

    (College of Information Science and Engineering, Northeastern University, Wenhua Road, NO. 3-11, Shenyang 110819, China
    Key Laboratory of Integrated Energy Optimization and Secure Operation of Liaoning Province, Northeastern University, Shenyang 110819, China)

  • Qi Tang

    (State Grid Jibei Electric Power Co. Ltd., Tangshan Power Supply Company, Jianshe Road, NO. 7, Tangshan 063000, China)

  • Bo Hu

    (State Grid Liaoning Electric Power Co. Ltd., Shenyang 110006, China)

  • Min Ma

    (State Grid Liaoning Electric Power Co. Ltd., Shenyang 110006, China)

Abstract

In a thermoelectric coupling energy system, renewable energy is often curtailed by the uncertainty of the power generation. Besides, the integration of renewable energy is restricted by the inflexible operation of combined heat and power units due to the strong coupling relationship between power generation and heating supply, especially in winter. Utilization of the district heating network, a heat storage feature, is a cost-effective measure to improve the overall system operational flexibility. In this paper, a new heat characteristic index is proposed in a district heating system, which is applied to measure the impact of the flexibility of combined heat and power units’ output. Furthermore, in order to increase the reliability of an electric power system, a probabilistic model of combined heat and power units’ spinning reserves capacity related to confidence level K is established. What is more, the two indexes K and thermal characteristic index have a coupled relationship. In addition, for model solving methodology, the discretized step transformation and constant mass flow and variables temperature method is adopted to transform the non-linear system model into linear programming form. Case studies are carried out to show the linkage between system costs, K and thermal characteristic index. The optimal result can achieve balance among the system reliability, flexibility and economy.

Suggested Citation

  • Guangdi Li & Qi Tang & Bo Hu & Min Ma, 2022. "Optimal Scheduling of Thermoelectric Coupling Energy System Considering Thermal Characteristics of DHN," Sustainability, MDPI, vol. 14(15), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9764-:d:883002
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9764/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/15/9764/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Liudong & Liu, Nian & Li, Chenchen & Wu, Lei & Chen, Yubing, 2021. "Multi-party stochastic energy scheduling for industrial integrated energy systems considering thermal delay and thermoelectric coupling," Applied Energy, Elsevier, vol. 304(C).
    2. Liao, Tianjun & Xu, Qidong & Dai, Yawen & Cheng, Chun & He, Qijiao & Ni, Meng, 2022. "Radiative cooling-assisted thermoelectric refrigeration and power systems: Coupling properties and parametric optimization," Energy, Elsevier, vol. 242(C).
    3. Zhang, Tong & Li, Zhigang & Wu, Q.H. & Zhou, Xiaoxin, 2019. "Decentralized state estimation of combined heat and power systems using the asynchronous alternating direction method of multipliers," Applied Energy, Elsevier, vol. 248(C), pages 600-613.
    4. Best, Robert E. & Rezazadeh Kalehbasti, P. & Lepech, Michael D., 2020. "A novel approach to district heating and cooling network design based on life cycle cost optimization," Energy, Elsevier, vol. 194(C).
    5. Li, Xue & Li, Wenming & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Li, Guoqing, 2020. "Collaborative scheduling and flexibility assessment of integrated electricity and district heating systems utilizing thermal inertia of district heating network and aggregated buildings," Applied Energy, Elsevier, vol. 258(C).
    6. Betancourt Schwarz, Manuel & Mabrouk, Mohamed Tahar & Santo Silva, Carlos & Haurant, Pierrick & Lacarrière, Bruno, 2019. "Modified finite volumes method for the simulation of dynamic district heating networks," Energy, Elsevier, vol. 182(C), pages 954-964.
    7. Lahdelma, Risto & Hakonen, Henri, 2003. "An efficient linear programming algorithm for combined heat and power production," European Journal of Operational Research, Elsevier, vol. 148(1), pages 141-151, July.
    8. Merlin, Kevin & Delaunay, Didier & Soto, Jérôme & Traonvouez, Luc, 2016. "Heat transfer enhancement in latent heat thermal storage systems: Comparative study of different solutions and thermal contact investigation between the exchanger and the PCM," Applied Energy, Elsevier, vol. 166(C), pages 107-116.
    9. Huang, Jinbo & Li, Zhigang & Wu, Q.H., 2017. "Coordinated dispatch of electric power and district heating networks: A decentralized solution using optimality condition decomposition," Applied Energy, Elsevier, vol. 206(C), pages 1508-1522.
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Pan, Bo & Qi, Shiqiang, 2020. "Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power," Applied Energy, Elsevier, vol. 275(C).
    2. Chen, Yuwei & Guo, Qinglai & Sun, Hongbin & Li, Zhengshuo & Pan, Zhaoguang & Wu, Wenchuan, 2019. "A water mass method and its application to integrated heat and electricity dispatch considering thermal inertias," Energy, Elsevier, vol. 181(C), pages 840-852.
    3. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Pan, Zhenning & Yu, Tao & Li, Jie & Qu, Kaiping & Yang, Bo, 2020. "Risk-averse real-time dispatch of integrated electricity and heat system using a modified approximate dynamic programming approach," Energy, Elsevier, vol. 198(C).
    5. Zhu, Mengshu & Li, Jinghua, 2022. "Integrated dispatch for combined heat and power with thermal energy storage considering heat transfer delay," Energy, Elsevier, vol. 244(PB).
    6. Aidong Zeng & Jiawei Wang & Yaheng Wan, 2023. "Coordinated Optimal Dispatch of Electricity and Heat Integrated Energy Systems Based on Fictitious Node Method," Energies, MDPI, vol. 16(18), pages 1-24, September.
    7. Jiawei Wang & Aidong Zeng & Yaheng Wan, 2023. "Multi-Time-Scale Optimal Scheduling of Integrated Energy System Considering Transmission Delay and Heat Storage of Heating Network," Sustainability, MDPI, vol. 15(19), pages 1-26, September.
    8. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    9. Skalyga, Mikhail & Wu, Qiuwei & Zhang, Menglin, 2021. "Uncertainty-fully-aware coordinated dispatch of integrated electricity and heat system," Energy, Elsevier, vol. 224(C).
    10. Putna, Ondřej & Janošťák, František & Šomplák, Radovan & Pavlas, Martin, 2018. "Demand modelling in district heating systems within the conceptual design of a waste-to-energy plant," Energy, Elsevier, vol. 163(C), pages 1125-1139.
    11. Uhlemair, Harald & Karschin, Ingo & Geldermann, Jutta, 2014. "Optimizing the production and distribution system of bioenergy villages," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 62-72.
    12. Rong, Aiying & Lahdelma, Risto, 2017. "An efficient model and algorithm for the transmission-constrained multi-site combined heat and power system," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1106-1117.
    13. Shahsavar, Amin & Al-Rashed, Abdullah A.A.A. & Entezari, Sajad & Sardari, Pouyan Talebizadeh, 2019. "Melting and solidification characteristics of a double-pipe latent heat storage system with sinusoidal wavy channels embedded in a porous medium," Energy, Elsevier, vol. 171(C), pages 751-769.
    14. Huang, Manyun & Wei, Zhinong & Lin, Yuzhang, 2022. "Forecasting-aided state estimation based on deep learning for hybrid AC/DC distribution systems," Applied Energy, Elsevier, vol. 306(PB).
    15. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    16. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    17. Huang, Jinbo & Li, Zhigang & Wu, Q.H., 2017. "Coordinated dispatch of electric power and district heating networks: A decentralized solution using optimality condition decomposition," Applied Energy, Elsevier, vol. 206(C), pages 1508-1522.
    18. Wei Wei & Yusong Guo & Kai Hou & Kai Yuan & Yi Song & Hongjie Jia & Chongbo Sun, 2021. "Distributed Thermal Energy Storage Configuration of an Urban Electric and Heat Integrated Energy System Considering Medium Temperature Characteristics," Energies, MDPI, vol. 14(10), pages 1-34, May.
    19. Mughees, Neelam & Jaffery, Mujtaba Hussain & Mughees, Anam & Ansari, Ejaz Ahmad & Mughees, Abdullah, 2023. "Reinforcement learning-based composite differential evolution for integrated demand response scheme in industrial microgrids," Applied Energy, Elsevier, vol. 342(C).
    20. Diana Isabel Berrocal & Juan Blandon Rodriguez & Maria De Los Angeles Ortega Del Rosario & Itamar Harris & Arthur M. James Rivas, 2024. "Heat Transfer Enhancements Assessment in Hot Water Generation with Phase Change Materials (PCMs): A Review," Energies, MDPI, vol. 17(10), pages 1-35, May.

    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:jsusta:v:14:y:2022:i:15:p:9764-:d:883002. 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.