IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v66y2016i1d10.1007_s10898-016-0403-y.html
   My bibliography  Save this article

Discrete-continuous optimization of heat network operating conditions in parallel operation of similar pumps at pumping stations

Author

Listed:
  • N. N. Novitsky

    (Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences)

  • A. V. Lutsenko

    (Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences)

Abstract

The paper addresses an optimization problem of hydraulic conditions of heat supply systems. The research shows that when the main methods of operation control, including the control of the number of connected pumps at pumping stations, are used this problem is reduced to a mixed discrete-continuous programming problem which involves a nonlinear objective function, nonlinear equality constraints and simple inequalities. The paper presents the basic principles of the methods for calculation of feasible and optimal conditions on the basis of continuous variables as a constituent of the suggested technique for solving the general problem. Consideration is given to four possible strategies to fraction and cut the variants while searching for solutions on the basis of discrete variables. The results of computational experiments illustrating the comparative efficiency of different strategies are presented.

Suggested Citation

  • N. N. Novitsky & A. V. Lutsenko, 2016. "Discrete-continuous optimization of heat network operating conditions in parallel operation of similar pumps at pumping stations," Journal of Global Optimization, Springer, vol. 66(1), pages 83-94, September.
    • Handle: RePEc:spr:jglopt:v:66:y:2016:i:1:d:10.1007_s10898-016-0403-y
    DOI: 10.1007/s10898-016-0403-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10898-016-0403-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10898-016-0403-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Hongtao & Burer, Meinrad & Song, Zhi-Ping & Favrat, Daniel & Marechal, Francois, 2004. "Green heating system: characteristics and illustration with multi-criteria optimization of an integrated energy system," Energy, Elsevier, vol. 29(2), pages 225-244.
    2. Jing, Z.X. & Jiang, X.S. & Wu, Q.H. & Tang, W.H. & Hua, B., 2014. "Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system," Energy, Elsevier, vol. 73(C), pages 399-415.
    3. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    4. Jiang, X.S. & Jing, Z.X. & Li, Y.Z. & Wu, Q.H. & Tang, W.H., 2014. "Modelling and operation optimization of an integrated energy based direct district water-heating system," Energy, Elsevier, vol. 64(C), pages 375-388.
    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. 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.
    2. 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.
    3. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Wang, Jinda, 2018. "Effects of the operation regulation modes of district heating system on an integrated heat and power dispatch system for wind power integration," Applied Energy, Elsevier, vol. 230(C), pages 1126-1139.
    4. Zhang, Lipeng & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Li, Hongwei & Li, Xiaopeng & Svendsen, Svend, 2016. "Method for reducing excess heat supply experienced in typical Chinese district heating systems by achieving hydraulic balance and improving indoor air temperature control at the building level," Energy, Elsevier, vol. 107(C), pages 431-442.
    5. Chen, Dongwen & Li, Yong & Abbas, Zulkarnain & Li, Dehong & Wang, Ruzhu, 2022. "Network flow calculation based on the directional nodal potential method for meshed heating networks," Energy, Elsevier, vol. 243(C).
    6. 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).
    7. Hohmann, Marc & Warrington, Joseph & Lygeros, John, 2020. "A moment and sum-of-squares extension of dual dynamic programming with application to nonlinear energy storage problems," European Journal of Operational Research, Elsevier, vol. 283(1), pages 16-32.
    8. Lake, Andrew & Rezaie, Behanz & Beyerlein, Steven, 2017. "Review of district heating and cooling systems for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 417-425.
    9. Wang, Wei & Jing, Sitong & Sun, Yang & Liu, Jizhen & Niu, Yuguang & Zeng, Deliang & Cui, Can, 2019. "Combined heat and power control considering thermal inertia of district heating network for flexible electric power regulation," Energy, Elsevier, vol. 169(C), pages 988-999.
    10. Liu, Mingzhe & Ooka, Ryozo & Choi, Wonjun & Ikeda, Shintaro, 2019. "Experimental and numerical investigation of energy saving potential of centralized and decentralized pumping systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    11. Li, Yu & Rezgui, Yacine & Zhu, Hanxing, 2017. "District heating and cooling optimization and enhancement – Towards integration of renewables, storage and smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 281-294.
    12. Zheng, J.H. & Chen, J.J. & Wu, Q.H. & Jing, Z.X., 2015. "Multi-objective optimization and decision making for power dispatch of a large-scale integrated energy system with distributed DHCs embedded," Applied Energy, Elsevier, vol. 154(C), pages 369-379.
    13. Sang Hwa Song & Taesu Cheong, 2018. "Pattern-Based Set Partitioning Algorithm for the Integrated Sustainable Operation of a District Heating Network," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    14. Li, Peng & Li, Shuang & Yu, Hao & Yan, Jinyue & Ji, Haoran & Wu, Jianzhong & Wang, Chengshan, 2022. "Quantized event-driven simulation for integrated energy systems with hybrid continuous-discrete dynamics," Applied Energy, Elsevier, vol. 307(C).
    15. 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).
    16. Wei, F. & Wu, Q.H. & Jing, Z.X. & Chen, J.J. & Zhou, X.X., 2016. "Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach," Energy, Elsevier, vol. 111(C), pages 933-946.
    17. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    18. Tahir, Muhammad Faizan & Haoyong, Chen & Guangze, Han, 2022. "Evaluating individual heating alternatives in integrated energy system by employing energy and exergy analysis," Energy, Elsevier, vol. 249(C).
    19. 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.
    20. Suyang Zhou & Di He & Zhiyang Zhang & Zhi Wu & Wei Gu & Junjie Li & Zhe Li & Gaoxiang Wu, 2019. "A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network," Sustainability, MDPI, vol. 11(23), pages 1-18, November.

    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:spr:jglopt:v:66:y:2016:i:1:d:10.1007_s10898-016-0403-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.