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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
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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    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. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
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