IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v144y2018icp472-481.html
   My bibliography  Save this article

Coupling optimization of urban spatial structure and neighborhood-scale distributed energy systems

Author

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

Abstract

When planning a neighborhood-scale distributed energy system (NDES), enough attention should be paid to the urban spatial structure, which may affect not only the system configuration on the supply side but also the load profiles on the demand side as well as their interactions. In this study, a novel nonlinear optimization model is developed for the determination of neighborhood design and NDES arrangement in terms of energy-saving aspect. By executing the optimization model, besides the configuration of energy supply technology, optimal building mix within the neighborhood can be also deduced. As an illustrative example, a mixed-use neighborhood located in Shanghai, China has been assumed for analysis. According to the simulation results, the introduction of NDES may achieve satisfied energy-saving benefits. Although additional energy consumption including heat loss and pump power may be encountered in the NDES, it can be offset through rational plan of the urban spatial structure and its cooperation with the supply side. For a fixed building mix, the reduction of supply radius may lead to better energy performance. Moreover, there exists the maximum supply radius over which, the NDES will not be recommended from the energy-saving viewpoint.

Suggested Citation

  • Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Coupling optimization of urban spatial structure and neighborhood-scale distributed energy systems," Energy, Elsevier, vol. 144(C), pages 472-481.
  • Handle: RePEc:eee:energy:v:144:y:2018:i:c:p:472-481
    DOI: 10.1016/j.energy.2017.12.076
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421732114X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.12.076?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. Tan, Dongwen & Zhou, Xinping & Xu, Yangyang & Wu, Cai & Li, Yong, 2017. "Environmental, health and economic benefits of using urban updraft tower to govern urban air pollution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1300-1308.
    2. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    3. Pan, Yu & Liu, Liuchen & Zhu, Tong & Zhang, Tao & Zhang, Junying, 2017. "Feasibility analysis on distributed energy system of Chongming County based on RETScreen software," Energy, Elsevier, vol. 130(C), pages 298-306.
    4. Roque Díaz, P. & Benito, Y.R. & Parise, J.A.R., 2010. "Thermoeconomic assessment of a multi-engine, multi-heat-pump CCHP (combined cooling, heating and power generation) system – A case study," Energy, Elsevier, vol. 35(9), pages 3540-3550.
    5. Gang, Wenjie & Wang, Shengwei & Gao, Diance & Xiao, Fu, 2015. "Performance assessment of district cooling systems for a new development district at planning stage," Applied Energy, Elsevier, vol. 140(C), pages 33-43.
    6. 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.
    7. Chow, T. T. & Chan, Apple L. S. & Song, C. L., 2004. "Building-mix optimization in district cooling system implementation," Applied Energy, Elsevier, vol. 77(1), pages 1-13, January.
    8. 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.
    9. Yamagata, Yoshiki & Seya, Hajime, 2013. "Simulating a future smart city: An integrated land use-energy model," Applied Energy, Elsevier, vol. 112(C), pages 1466-1474.
    10. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-criteria assessment of building combined heat and power systems located in different climate zones: Japan–China comparison," Energy, Elsevier, vol. 103(C), pages 502-512.
    11. Yokoyama, Ryohei & Nakamura, Ryo & Wakui, Tetsuya, 2017. "Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 137(C), pages 878-887.
    12. 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.
    13. Best, Robert E. & Flager, Forest & Lepech, Michael D., 2015. "Modeling and optimization of building mix and energy supply technology for urban districts," Applied Energy, Elsevier, vol. 159(C), pages 161-177.
    14. Zhang, Yin & Wang, Xin & Zhuo, Siwen & Zhang, Yinping, 2016. "Pre-feasibility of building cooling heating and power system with thermal energy storage considering energy supply–demand mismatch," Applied Energy, Elsevier, vol. 167(C), pages 125-134.
    15. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    16. 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.
    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. Wang, Luhao & Li, Qiqiang & Ding, Ran & Sun, Mingshun & Wang, Guirong, 2017. "Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach," Energy, Elsevier, vol. 130(C), pages 1-14.
    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. Bahl, Björn & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "Optimization-based identification and quantification of demand-side management potential for distributed energy supply systems," Energy, Elsevier, vol. 135(C), pages 889-899.
    21. 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.
    22. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    23. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    24. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    2. Bernadette Fina & Hans Auer, 2020. "Economic Viability of Renewable Energy Communities under the Framework of the Renewable Energy Directive Transposed to Austrian Law," Energies, MDPI, vol. 13(21), pages 1-31, November.
    3. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    4. Liu, Wen Hui & Ho, Wai Shin & Lee, Ming Yang & Hashim, Haslenda & Lim, Jeng Shiun & Klemeš, Jiří J. & Mah, Angel Xin Yee, 2019. "Development and optimization of an integrated energy network with centralized and decentralized energy systems using mathematical modelling approach," Energy, Elsevier, vol. 183(C), pages 617-629.
    5. Kılkış, Şiir & Kılkış, Birol, 2019. "An urbanization algorithm for districts with minimized emissions based on urban planning and embodied energy towards net-zero exergy targets," Energy, Elsevier, vol. 179(C), pages 392-406.
    6. Fina, Bernadette & Auer, Hans & Friedl, Werner, 2019. "Profitability of PV sharing in energy communities: Use cases for different settlement patterns," Energy, Elsevier, vol. 189(C).
    7. Chicherin, Stanislav & Anvari-Moghaddam, Amjad, 2021. "Adjusting heat demands using the operational data of district heating systems," Energy, Elsevier, vol. 235(C).
    8. Ying Zhu & Quanling Tong & Xueting Zeng & Xiaxia Yan & Yongping Li & Guohe Huang, 2019. "Optimal Design of a Distributed Energy System Using the Functional Interval Model That Allows Reduced Carbon Emissions in Guanzhong, a Rural Area of China," Sustainability, MDPI, vol. 11(7), pages 1-22, April.
    9. Fanyue Qian & Weijun Gao & Dan Yu & Yongwen Yang & Yingjun Ruan, 2022. "An Analysis of the Potential of Hydrogen Energy Technology on Demand Side Based on a Carbon Tax: A Case Study in Japan," Energies, MDPI, vol. 16(1), pages 1-23, December.
    10. David Morillón Gálvez & Iván García Kerdan & Germán Carmona-Paredes, 2022. "Assessing the Potential of Implementing a Solar-Based Distributed Energy System for a University Using the Campus Bus Stops," Energies, MDPI, vol. 15(10), pages 1-16, May.
    11. Kachirayil, Febin & Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2022. "Reviewing local and integrated energy system models: insights into flexibility and robustness challenges," Applied Energy, Elsevier, vol. 324(C).
    12. Wolsink, Maarten, 2020. "Distributed energy systems as common goods: Socio-political acceptance of renewables in intelligent microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).

    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. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    2. Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
    3. Wakui, Tetsuya & Hashiguchi, Moe & Yokoyama, Ryohei, 2021. "Structural design of distributed energy networks by a hierarchical combination of variable- and constraint-based decomposition methods," Energy, Elsevier, vol. 224(C).
    4. 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.
    5. 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.
    6. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    7. 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.
    8. Clarke, Fiona & Dorneanu, Bogdan & Mechleri, Evgenia & Arellano-Garcia, Harvey, 2021. "Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems," Energy, Elsevier, vol. 235(C).
    9. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    10. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2017. "Benefit allocation for distributed energy network participants applying game theory based solutions," Energy, Elsevier, vol. 119(C), pages 384-391.
    11. 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.
    12. 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.
    13. 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.
    14. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    15. Alberto Fichera & Mattia Frasca & Rosaria Volpe, 2020. "A cost-based approach for evaluating the impact of a network of distributed energy systems on the centralized energy supply," Energy & Environment, , vol. 31(1), pages 77-87, February.
    16. 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.
    17. Jalil-Vega, Francisca & Hawkes, Adam D., 2018. "The effect of spatial resolution on outcomes from energy systems modelling of heat decarbonisation," Energy, Elsevier, vol. 155(C), pages 339-350.
    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. 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.
    20. 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.

    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:144:y:2018:i:c:p:472-481. 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.