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Regional Variations in Energy Consumption of Appliances: Conditional Demand Analysis Applied to Brazilian Households

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  • Marcos Lins
  • Angela da Silva
  • Luiz Rosa

Abstract

Estimating the true consumption of appliances in use is important both for modeling and short term forecasting of electricity demand, as well as for planning and assessing Demand Side Management (DSM). This paper applies the new technique known as Conditional Demand Analysis (CDA) to estimate consumption of these appliances. This was made possible due to a major survey carried out for the Brazilian National Electricity Conservation Program by the Brazilian electric utility companies while they were still state owned. Results were checked against traditional appliance energy consumption figures, and investigations carried out to ascertain if differences were due to regional variations in consumption patterns from northern to southern Brazil. Copyright Kluwer Academic Publishers 2002

Suggested Citation

  • Marcos Lins & Angela da Silva & Luiz Rosa, 2002. "Regional Variations in Energy Consumption of Appliances: Conditional Demand Analysis Applied to Brazilian Households," Annals of Operations Research, Springer, vol. 117(1), pages 235-246, November.
    • Handle: RePEc:spr:annopr:v:117:y:2002:i:1:p:235-246:10.1023/a:1021533809914
    DOI: 10.1023/A:1021533809914
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    Citations

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    Cited by:

    1. Hannah Goozee, 2017. "Energy, poverty and development: a primer for the Sustainable Development Goals," Working Papers 156, International Policy Centre for Inclusive Growth.
    2. Huse, Cristian & Lucinda, Claudio & Cardoso, Andre Ribeiro, 2020. "Consumer response to energy label policies: Evidence from the Brazilian energy label program," Energy Policy, Elsevier, vol. 138(C).
    3. Hannah Goozee, 2017. "Energy, Poverty and Development: A Primer for the Sustainable Development Goals," Working Papers id:11933, eSocialSciences.
    4. Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
    5. Shen, Pengyuan & Yang, Biao, 2020. "Projecting Texas energy use for residential sector under future climate and urbanization scenarios: A bottom-up method based on twenty-year regional energy use data," Energy, Elsevier, vol. 193(C).
    6. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.

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