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Sustainable cities - modelling urban energy supply and demand

Author

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  • Brownsword, R.A.
  • Fleming, P.D.
  • Powell, J.C.
  • Pearsall, N.

Abstract

A model of urban energy consumption has been developed using energy supply data and post-code information. The model simulates spatial and diurnal variations in energy demand, and also models the effect of energy-management measures and associated reductions in CO2 emissions. A linear programming optimisation module is used to identify the most cost-effective measures to achieve specified CO2 or energy reduction-targets. When combined with data from an associated attitudinal survey, the model can be used to assess the potential for CO2 reduction in the urban environment.

Suggested Citation

  • Brownsword, R.A. & Fleming, P.D. & Powell, J.C. & Pearsall, N., 2005. "Sustainable cities - modelling urban energy supply and demand," Applied Energy, Elsevier, vol. 82(2), pages 167-180, October.
    • Handle: RePEc:eee:appene:v:82:y:2005:i:2:p:167-180
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    1. Fleming, P. D. & Webber, P. H., 2004. "Local and regional greenhouse gas management," Energy Policy, Elsevier, vol. 32(6), pages 761-771, April.
    2. Bennett, M. & Newborough, M., 2001. "Auditing energy use in cities," Energy Policy, Elsevier, vol. 29(2), pages 125-134, January.
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    Cited by:

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    3. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    4. Voulis, Nina & Warnier, Martijn & Brazier, Frances M.T., 2018. "Understanding spatio-temporal electricity demand at different urban scales: A data-driven approach," Applied Energy, Elsevier, vol. 230(C), pages 1157-1171.
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    7. Roth, Jonathan & Martin, Amory & Miller, Clayton & Jain, Rishee K., 2020. "SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods," Applied Energy, Elsevier, vol. 280(C).
    8. Liu, Xiaoping & Ou, Jinpei & Chen, Yimin & Wang, Shaojian & Li, Xia & Jiao, Limin & Liu, Yaolin, 2019. "Scenario simulation of urban energy-related CO2 emissions by coupling the socioeconomic factors and spatial structures," Applied Energy, Elsevier, vol. 238(C), pages 1163-1178.
    9. Shimoda, Yoshiyuki & Asahi, Takahiro & Taniguchi, Ayako & Mizuno, Minoru, 2007. "Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model," Energy, Elsevier, vol. 32(9), pages 1617-1633.
    10. Radulovic, Dusko & Skok, Srdjan & Kirincic, Vedran, 2011. "Energy efficiency public lighting management in the cities," Energy, Elsevier, vol. 36(4), pages 1908-1915.
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    12. Porse, Erik & Derenski, Joshua & Gustafson, Hannah & Elizabeth, Zoe & Pincetl, Stephanie, 2016. "Structural, geographic, and social factors in urban building energy use: Analysis of aggregated account-level consumption data in a megacity," Energy Policy, Elsevier, vol. 96(C), pages 179-192.
    13. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2018. "Modelling urban energy requirements using open source data and models," Applied Energy, Elsevier, vol. 231(C), pages 1100-1108.
    14. Theodoridou, Ifigeneia & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "A feasibility evaluation tool for sustainable cities – A case study for Greece," Energy Policy, Elsevier, vol. 44(C), pages 207-216.
    15. Yu, Dongwei & Tan, Hongwei & Ruan, Yingjun, 2012. "An improved two-step floating catchment area method for supporting district building energy planning: A case study of Yongding County city, China," Applied Energy, Elsevier, vol. 95(C), pages 156-163.
    16. Mikkola, Jani & Lund, Peter D., 2014. "Models for generating place and time dependent urban energy demand profiles," Applied Energy, Elsevier, vol. 130(C), pages 256-264.
    17. Kontokosta, Constantine E. & Tull, Christopher, 2017. "A data-driven predictive model of city-scale energy use in buildings," Applied Energy, Elsevier, vol. 197(C), pages 303-317.
    18. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    19. Facchini, Angelo & Kennedy, Chris & Stewart, Iain & Mele, Renata, 2017. "The energy metabolism of megacities," Applied Energy, Elsevier, vol. 186(P2), pages 86-95.
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    21. Zhang, Yan & Yang, Zhifeng & Fath, Brian D. & Li, Shengsheng, 2010. "Ecological network analysis of an urban energy metabolic system: Model development, and a case study of four Chinese cities," Ecological Modelling, Elsevier, vol. 221(16), pages 1865-1879.

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