IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p10053-d1523564.html
   My bibliography  Save this article

Application of Distributed Collaborative Optimization in Building Multi-Energy Complementary Energy Systems

Author

Listed:
  • Yongchao Zhao

    (School of Management, China University of Mining & Technology, Beijing 100083, China)

  • Yang Yang

    (School of Management, China University of Mining & Technology, Beijing 100083, China)

  • Jianmin Zhang

    (School of Management, China University of Mining & Technology, Beijing 100083, China)

  • Hugeng Ling

    (Guizhou Environmental Energy Exchange Co., Ltd., Guiyang 550000, China)

  • Yawei Du

    (Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China)

Abstract

This article investigates the application and physical mechanism exploration of distributed collaborative optimization algorithms in building multi-energy complementary energy systems, in response to the difficulties in coordinating various subsystems and insufficient dynamic control strategies. On the basis of modeling each subsystem, the Dual Decomposition algorithm is used to decompose the global optimization problem of the system into several independent sub problems, achieving independent optimization of each subsystem. Through an adaptive dynamic scheduling strategy, real-time data and predictive information are continuously updated and controlled, effectively allocating system resources. The experimental results show that compared to the original system before optimization, the improved algorithm in this paper reduces the total energy consumption of the system by 6.9% and 2.8% on typical summer and winter days, respectively. The conclusion shows that the algorithm proposed in this paper can effectively solve the problem of system coordination difficulties, improve system resource allocation and overall operation level, and provide a new perspective for the optimization design and operation control of energy systems.

Suggested Citation

  • Yongchao Zhao & Yang Yang & Jianmin Zhang & Hugeng Ling & Yawei Du, 2024. "Application of Distributed Collaborative Optimization in Building Multi-Energy Complementary Energy Systems," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:10053-:d:1523564
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/10053/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/22/10053/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
    2. Qicong Cai & Baizhan Li & Wenbo He & Miao Guo, 2024. "Energy Consumption Calculation of Civil Buildings in Regional Integrated Energy Systems: A Review of Characteristics, Methods and Application Prospects," Sustainability, MDPI, vol. 16(13), pages 1-25, July.
    3. Lee, Inkyu & Tester, Jefferson William & You, Fengqi, 2019. "Systems analysis, design, and optimization of geothermal energy systems for power production and polygeneration: State-of-the-art and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 551-577.
    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. Tian, Xueyu & You, Fengqi, 2019. "Carbon-neutral hybrid energy systems with deep water source cooling, biomass heating, and geothermal heat and power," Applied Energy, Elsevier, vol. 250(C), pages 413-432.
    2. Mahmoudan, Alireza & Samadof, Parviz & Hosseinzadeh, Siamak & Garcia, Davide Astiaso, 2021. "A multigeneration cascade system using ground-source energy with cold recovery: 3E analyses and multi-objective optimization," Energy, Elsevier, vol. 233(C).
    3. Reyes-Antonio, Claudio Antonio & Iglesias-Silva, Gustavo Arturo & Rubio-Maya, Carlos & Fuentes-Cortés, Luis Fabián, 2024. "Multi-objective design of off-grid low-enthalpy geothermal generation systems considering partial-load operations," Energy, Elsevier, vol. 294(C).
    4. Ma, Ting & Guo, Zhixiong & Lin, Mei & Wang, Qiuwang, 2021. "Recent trends on nanofluid heat transfer machine learning research applied to renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. Zhao, Wenna & Ma, Kai & Yang, Jie & Guo, Shiliang, 2024. "A multi-time scale demand response scheme based on noncooperative game for economic operation of industrial park," Energy, Elsevier, vol. 302(C).
    6. Schifflechner, Christopher & Kuhnert, Lara & Irrgang, Ludwig & Dawo, Fabian & Kaufmann, Florian & Wieland, Christoph & Spliethoff, Hartmut, 2023. "Geothermal trigeneration systems with Organic Rankine Cycles: Evaluation of different plant configurations considering part load behaviour," Renewable Energy, Elsevier, vol. 207(C), pages 218-233.
    7. Schilling, J. & Entrup, M. & Hopp, M. & Gross, J. & Bardow, A., 2021. "Towards optimal mixtures of working fluids: Integrated design of processes and mixtures for Organic Rankine Cycles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    8. Vaccari, Marco & Pannocchia, Gabriele & Tognotti, Leonardo & Paci, Marco, 2023. "Rigorous simulation of geothermal power plants to evaluate environmental performance of alternative configurations," Renewable Energy, Elsevier, vol. 207(C), pages 471-483.
    9. Vaccari, Marco & Pannocchia, Gabriele & Tognotti, Leonardo & Paci, Marco & Bonciani, Roberto, 2020. "A rigorous simulation model of geothermal power plants for emission control," Applied Energy, Elsevier, vol. 263(C).
    10. Wang, Yongzhen & Li, Chengjun & Zhao, Jun & Wu, Boyuan & Du, Yanping & Zhang, Jing & Zhu, Yilin, 2021. "The above-ground strategies to approach the goal of geothermal power generation in China: State of art and future researches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    11. Zhao, Ning & You, Fengqi, 2020. "Can renewable generation, energy storage and energy efficient technologies enable carbon neutral energy transition?," Applied Energy, Elsevier, vol. 279(C).
    12. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
    13. Jia, Zhiyang & Jin, Xinqiao & Lyu, Yuan & Xue, Qi & Du, Zhimin, 2023. "A robust capacity configuration selection method of multiple-chiller system concerned with the uncertainty of annual hourly load profile," Energy, Elsevier, vol. 282(C).
    14. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    15. Eyerer, Sebastian & Dawo, Fabian & Schifflechner, Christopher & Niederdränk, Anne & Spliethoff, Hartmut & Wieland, Christoph, 2022. "Experimental evaluation of an ORC-CHP architecture based on regenerative preheating for geothermal applications," Applied Energy, Elsevier, vol. 315(C).
    16. Hasanien, Hany M. & Alsaleh, Ibrahim & Tostado-Véliz, Marcos & Zhang, Miao & Alateeq, Ayoob & Jurado, Francisco & Alassaf, Abdullah, 2024. "Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles," Energy, Elsevier, vol. 286(C).
    17. Chen, Wei-Han & You, Fengqi, 2022. "Sustainable building climate control with renewable energy sources using nonlinear model predictive control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    18. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    19. Feili, Milad & Rostamzadeh, Hadi & Ghaebi, Hadi, 2020. "A new high-efficient cooling/power cogeneration system based on a double-flash geothermal power plant and a novel zeotropic bi-evaporator ejector refrigeration cycle," Renewable Energy, Elsevier, vol. 162(C), pages 2126-2152.
    20. Sun, Li & Jin, Yuhui & You, Fengqi, 2020. "Active disturbance rejection temperature control of open-cathode proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 261(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:jsusta:v:16:y:2024:i:22:p:10053-:d:1523564. 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.