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Energy Planning in the Big Data Era: A Theme Study of the Residential Sector

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  • Estiri, Hossein

Abstract

This paper re-conceptualizes the planning process in the big data era based on the improvements that non-linear modeling approaches provide over the mainstream linear approaches. First, it demonstrates challenges of conventional linear methodologies in modeling complexities of residential energy use, addressing the “variety” from the three Vs of big data. Suggesting a non-linear modeling schema to analyze household energy use, the paper develops its discussion around the repercussions of the use of non-linear modeling in energy policy and planning. Planners / policy-makers are not often equipped with the tools needed to translate complex scientific outcomes into policies. To fill this gap, this work proposes modifications in the traditional planning process in order to be able to benefit from the abundance of data and the advances in analytical methodologies. The conclusion section introduces three short-term repercussions of this work for energy policy (and planning, in general) in the big data era: tool development, data infrastructures, and planning education.

Suggested Citation

  • Estiri, Hossein, 2014. "Energy Planning in the Big Data Era: A Theme Study of the Residential Sector," EconStor Conference Papers 106936, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esconf:106936
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    File URL: https://www.econstor.eu/bitstream/10419/106936/1/Planning%20in%20the%20Big%20Data%20Era%20-Proceeding%20.pdf
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    References listed on IDEAS

    as
    1. Scott Kelly, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector," Working Papers EPRG 1117, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    2. Kelly, Scott, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model of the English residential sector," Energy, Elsevier, vol. 36(9), pages 5610-5620.
    3. Eric Hirst, 1980. "Review of Data Related to Energy Use in Residential and Commercial Buildings," Management Science, INFORMS, vol. 26(9), pages 857-870, September.
    4. Aune, Margrethe, 2007. "Energy comes home," Energy Policy, Elsevier, vol. 35(11), pages 5457-5465, November.
    5. Lutzenhiser, Loren, 1992. "A cultural model of household energy consumption," Energy, Elsevier, vol. 17(1), pages 47-60.
    6. Jihoon Min & Zeke Hausfather & Qi Feng Lin, 2010. "A High‐Resolution Statistical Model of Residential Energy End Use Characteristics for the United States," Journal of Industrial Ecology, Yale University, vol. 14(5), pages 791-807, October.
    7. Brounen, Dirk & Kok, Nils & Quigley, John M., 2012. "Residential energy use and conservation: Economics and demographics," European Economic Review, Elsevier, vol. 56(5), pages 931-945.
    8. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Energy Policy; Residential Buildings; Non-Linear Modeling; Big Data; Planning Process;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy

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