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Structural modelling of energy demand in the residential sector: 1. Development of structural models

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  • Michalik, G.
  • Khan, M.E.
  • Bonwick, W.J.
  • Mielczarski, W.

Abstract

We present the development of structural models for energy consumption in the residential sector. Customers were segmented into four main categories with six sub-groups within each category. A survey of over 100 customers provided data on the 17 appliances considered, which are grouped into three main categories. The models provide energy-use patterns for each category of customers for selected customer samples or for a chosen area. Energy patterns are simulated in 15-min time intervals. These show total demand and provide information on the structure of energy consumption in simulations for demand-management programs, long-term forecasting and customer identification.

Suggested Citation

  • Michalik, G. & Khan, M.E. & Bonwick, W.J. & Mielczarski, W., 1997. "Structural modelling of energy demand in the residential sector: 1. Development of structural models," Energy, Elsevier, vol. 22(10), pages 937-947.
    • Handle: RePEc:eee:energy:v:22:y:1997:i:10:p:937-947
    DOI: 10.1016/S0360-5442(97)00029-7
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    Citations

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    Cited by:

    1. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    2. 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.
    3. Kumar, Ujjwal & Jain, V.K., 2010. "Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India," Energy, Elsevier, vol. 35(4), pages 1709-1716.
    4. Clinch, J. Peter & Healy, John D., 2003. "Valuing improvements in comfort from domestic energy-efficiency retrofits using a trade-off simulation model," Energy Economics, Elsevier, vol. 25(5), pages 565-583, September.
    5. Hayn, Marian & Bertsch, Valentin & Zander, Anne & Nickel, Stefan & Fichtner, Wolf, 2016. "The impact of electricity tariffs on residential demand side flexibility," Working Paper Series in Production and Energy 14, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    6. 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.
    7. Hawkes, Adam & Leach, Matthew, 2005. "Impacts of temporal precision in optimisation modelling of micro-Combined Heat and Power," Energy, Elsevier, vol. 30(10), pages 1759-1779.
    8. Beccali, M. & Cellura, M. & Lo Brano, V. & Marvuglia, A., 2008. "Short-term prediction of household electricity consumption: Assessing weather sensitivity in a Mediterranean area," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(8), pages 2040-2065, October.
    9. Egelioglu, F. & Mohamad, A.A. & Guven, H., 2001. "Economic variables and electricity consumption in Northern Cyprus," Energy, Elsevier, vol. 26(4), pages 355-362.

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