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Integrating Direct Metering And Conditional Demand Analysis Fr Estimating End-Use Loads

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Author Info

  • BARTELS, R.
  • FIEBIG, D.G.

Abstract

Conditional demand analysis (CDA) is a statistical method for allocating the total household electricity load during a period, into its constituent components, each associated with a particular electricity-using appliance or end-use. This is an indirect approach to the estimation of end-use demand and, quite naturally, it often generates imprecise estimates. One of the possible methods for improving these estimates involves the incorporation of data obtained by directly metering specific appliances. It is argued that an extremely natural approach to the use of this extra information follows directly from a reformulation of the standard CDA model into a random coefficient framework Some new results on the possible efficiency gains from such an approach are developed. Illustrations based on an empirical study of New South Wales (NSW) households are also provided.

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Bibliographic Info

Paper provided by Tilburg - Center for Economic Research in its series Papers with number 9056.

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Length: 21 pages
Date of creation: 1990
Date of revision:
Handle: RePEc:fth:tilbur:9056

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Keywords: estimator ; demand ; electricity;

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Cited by:
  1. Hanne Marit Dalen & Bodil M. Larsen, 2013. "Residential end-use electricity demand. Development over time," Discussion Papers 736, Research Department of Statistics Norway.
  2. Muhammad, Akmal, 2002. "The structure of consumer energy demand in Australia: an application of a dynamic almost ideal demand system," 2002 Conference (46th), February 13-15, 2002, Canberra 125050, Australian Agricultural and Resource Economics Society.
  3. Bartels, Robert & Fiebig, Denzil G., 1995. "Optimal design in end-use metering experiments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 305-309.
  4. Narayan, Paresh Kumar & Smyth, Russell, 2005. "The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 33(4), pages 467-474, March.
  5. Muhammad Akmal & David I. Stern, 2001. "Residential energy demand in Australia: an application of dynamic OLS," Working Papers in Ecological Economics 0104, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
  6. Bodil M. Larsen & Runa Nesbakken, 2003. "How to quantify household electricity end-use consumption," Discussion Papers 346, Research Department of Statistics Norway.
  7. Larsen, Bodil Merethe & Nesbakken, Runa, 2004. "Household electricity end-use consumption: results from econometric and engineering models," Energy Economics, Elsevier, vol. 26(2), pages 179-200, March.
  8. Muhammad Akmal & David I. Stern, 2001. "The structure of Australian residential energy demand," Working Papers in Ecological Economics 0101, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.

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