IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v109y2016icp353-364.html
   My bibliography  Save this article

Multi-objective optimization of a distributed energy network integrated with heating interchange

Author

Listed:
  • Wu, Qiong
  • Ren, Hongbo
  • Gao, Weijun
  • Ren, Jianxing

Abstract

In this study, a multi-objective MILP (mixed integer linear programming) model has been developed for the optimization of a distributed energy network integrated with heating interchanges. The model allows to determine the energy generation components among various candidates, the site and size of each selected technology, optimal running schedule, as well as optimal lay-out of heating pipelines. Both economic and environmental aspects have been taken into account in the objective function with relative weighting factors. As an illustrative example, the model is applied to a low carbon community including five buildings (hotel, hospital, office, store and apartment) located in Shanghai, China. According to the simulation results, by introducing the distributed energy network, the total capacity of distributed generations is increased, and the overall performances (both economic and environmental ones) of the local area are enhanced. In addition, the sensitivity analyses indicate that the determination of user preference, as well as the fluctuation of energy loads and fuel prices may have considerable influence on the performances of the distributed energy network. Moreover, according to the results of “8 buildings” cases with different building combinations, the rational selection of end-users is of vital importance for the plan and design of a distributed energy network.

Suggested Citation

  • Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-objective optimization of a distributed energy network integrated with heating interchange," Energy, Elsevier, vol. 109(C), pages 353-364.
    • Handle: RePEc:eee:energy:v:109:y:2016:i:c:p:353-364
    DOI: 10.1016/j.energy.2016.04.112
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216305321
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.04.112?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. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    2. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
    3. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    4. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
    5. Zahedi, A., 2011. "Maximizing solar PV energy penetration using energy storage technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 866-870, January.
    6. Li, Yajun & Xia, Yan, 2013. "DES/CCHP: The best utilization mode of natural gas for China’s low carbon economy," Energy Policy, Elsevier, vol. 53(C), pages 477-483.
    7. Buoro, D. & Casisi, M. & De Nardi, A. & Pinamonti, P. & Reini, M., 2013. "Multicriteria optimization of a distributed energy supply system for an industrial area," Energy, Elsevier, vol. 58(C), pages 128-137.
    8. Rieder, Andreas & Christidis, Andreas & Tsatsaronis, George, 2014. "Multi criteria dynamic design optimization of a small scale distributed energy system," Energy, Elsevier, vol. 74(C), pages 230-239.
    9. Kang, Lixia & Liu, Yongzhong, 2015. "Multi-objective optimization on a heat exchanger network retrofit with a heat pump and analysis of CO2 emissions control," Applied Energy, Elsevier, vol. 154(C), pages 696-708.
    10. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    11. Obara, Shin’ya & morizane, Yuta & Morel, Jorge, 2013. "A study of small-scale energy networks of the Japanese Syowa Base in Antarctica by distributed engine generators," Applied Energy, Elsevier, vol. 111(C), pages 113-128.
    12. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    13. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    14. Krajacic, Goran & Duic, Neven & Tsikalakis, Antonis & Zoulias, Manos & Caralis, George & Panteri, Eirini & Carvalho, Maria da Graça, 2011. "Feed-in tariffs for promotion of energy storage technologies," Energy Policy, Elsevier, vol. 39(3), pages 1410-1425, March.
    15. Shimizu, Teruyuki & Kikuchi, Yasunori & Sugiyama, Hirokazu & Hirao, Masahiko, 2015. "Design method for a local energy cooperative network using distributed energy technologies," Applied Energy, Elsevier, vol. 154(C), pages 781-793.
    16. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    17. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    18. Steen, David & Stadler, Michael & Cardoso, Gonçalo & Groissböck, Markus & DeForest, Nicholas & Marnay, Chris, 2015. "Modeling of thermal storage systems in MILP distributed energy resource models," Applied Energy, Elsevier, vol. 137(C), pages 782-792.
    19. Lesser, Jonathan A. & Su, Xuejuan, 2008. "Design of an economically efficient feed-in tariff structure for renewable energy development," Energy Policy, Elsevier, vol. 36(3), pages 981-990, March.
    20. Wakui, Tetsuya & Yokoyama, Ryohei, 2012. "Optimal sizing of residential SOFC cogeneration system for power interchange operation in housing complex from energy-saving viewpoint," Energy, Elsevier, vol. 41(1), pages 65-74.
    21. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    22. Zhou, Kaile & Yang, Shanlin & Chen, Zhiqiang & Ding, Shuai, 2014. "Optimal load distribution model of microgrid in the smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 304-310.
    23. 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.
    24. Meybodi, Mehdi Aghaei & Behnia, Masud, 2013. "Australian coal mine methane emissions mitigation potential using a Stirling engine-based CHP system," Energy Policy, Elsevier, vol. 62(C), pages 10-18.
    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. Miao Li & Yiran Feng & Maojun Zhou & Hailin Mu & Longxi Li & Yajun Wang, 2019. "Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network," Energies, MDPI, vol. 12(10), pages 1-19, May.
    2. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    3. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    4. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    5. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing & Lao, Changshi, 2017. "Profit allocation analysis among the distributed energy network participants based on Game-theory," Energy, Elsevier, vol. 118(C), pages 783-794.
    6. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    7. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    8. Mashayekh, Salman & Stadler, Michael & Cardoso, Gonçalo & Heleno, Miguel, 2017. "A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids," Applied Energy, Elsevier, vol. 187(C), pages 154-168.
    9. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    10. Wakui, Tetsuya & Yokoyama, Ryohei, 2014. "Optimal structural design of residential cogeneration systems in consideration of their operating restrictions," Energy, Elsevier, vol. 64(C), pages 719-733.
    11. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    12. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
    13. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    14. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    15. Wakui, Tetsuya & Kinoshita, Takahiro & Yokoyama, Ryohei, 2014. "A mixed-integer linear programming approach for cogeneration-based residential energy supply networks with power and heat interchanges," Energy, Elsevier, vol. 68(C), pages 29-46.
    16. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    17. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    18. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    19. Zhigang Duan & Yamin Yan & Xiaohan Yan & Qi Liao & Wan Zhang & Yongtu Liang & Tianqi Xia, 2017. "An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand," Energies, MDPI, vol. 11(1), pages 1-23, December.
    20. Marquant, Julien F. & Evins, Ralph & Bollinger, L. Andrew & Carmeliet, Jan, 2017. "A holarchic approach for multi-scale distributed energy system optimisation," Applied Energy, Elsevier, vol. 208(C), pages 935-953.

    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:eee:energy:v:109:y:2016:i:c:p:353-364. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.