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Capturing spatial effects, technology interactions, and uncertainty in urban energy and carbon models: Retrofitting newcastle as a case-study

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  • Keirstead, James
  • Calderon, Carlos

Abstract

Local authorities often rely upon urban energy and carbon modelling tools to develop mitigation policies and strategies that will deliver reductions in greenhouse gas emissions. In this paper the UK example of Newcastle-upon-Tyne is used to critique current practice, noting that important features of urban energy systems are often omitted by bottom-up tools including interactions between technologies, spatial disaggregation of demand, and the ability to pursue over-arching policy goals like cost minimization. An alternative optimization-based approach is then described and applied to the Newcastle case, at the scale of both the whole city and the South Heaton district, and using Monte Carlo techniques to address policy uncertainty. The results show that this new method can help policy makers draw more robust policy conclusions, sensitive to spatial variations in energy demand and capturing the interactions between developments in the national energy system and local policy options. Further work should focus on improving our understanding of local building stocks and energy demands so as to better assess the potential of new technologies and policies.

Suggested Citation

  • Keirstead, James & Calderon, Carlos, 2012. "Capturing spatial effects, technology interactions, and uncertainty in urban energy and carbon models: Retrofitting newcastle as a case-study," Energy Policy, Elsevier, vol. 46(C), pages 253-267.
  • Handle: RePEc:eee:enepol:v:46:y:2012:i:c:p:253-267
    DOI: 10.1016/j.enpol.2012.03.058
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    References listed on IDEAS

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    6. Kikegawa, Yukihiro & Genchi, Yutaka & Kondo, Hiroaki & Hanaki, Keisuke, 2006. "Impacts of city-block-scale countermeasures against urban heat-island phenomena upon a building's energy-consumption for air-conditioning," Applied Energy, Elsevier, vol. 83(6), pages 649-668, June.
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    Cited by:

    1. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    2. Morlet, Clémence & Keirstead, James, 2013. "A comparative analysis of urban energy governance in four European cities," Energy Policy, Elsevier, vol. 61(C), pages 852-863.
    3. Hargreaves, Anthony & Cheng, Vicky & Deshmukh, Sandip & Leach, Matthew & Steemers, Koen, 2017. "Forecasting how residential urban form affects the regional carbon savings and costs of retrofitting and decentralized energy supply," Applied Energy, Elsevier, vol. 186(P3), pages 549-561.
    4. repec:eee:appene:v:210:y:2018:i:c:p:1051-1072 is not listed on IDEAS
    5. Samsatli, Sheila & Samsatli, Nouri J. & Shah, Nilay, 2015. "BVCM: A comprehensive and flexible toolkit for whole system biomass value chain analysis and optimisation – Mathematical formulation," Applied Energy, Elsevier, vol. 147(C), pages 131-160.
    6. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.

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    Keywords

    Urban energy systems; Optimization; Retrofit;

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