Title: Effects of socioeconomic factors on household appliance, lighting, and space cooling electricity consumption

Authors: Merih Aydinalp, V. Ismet Ugursal, Alan S. Fung

Addresses: Itron, Inc., 20 Park Plaza, Suite 910, Boston, MA 02116, USA. ' Canadian Residential Energy End-use Data and Analysis Centre, Department of Mechanical Engineering, Dalhousie University, P.O. Box 1000, Halifax, N.S., B3J 2X4, Canada. ' Canadian Residential Energy End-use Data and Analysis Centre, Department of Mechanical Engineering, Dalhousie University, P.O. Box 1000, Halifax, N.S., B3J 2X4, Canada

Abstract: Two methods are currently used to model residential energy consumption at the national or regional level: the engineering method and the conditional demand analysis (CDA) method. One of the major difficulties associated with the use of engineering models is the inclusion of consumer behaviour and socioeconomic factors that have significant effects on the residential energy consumption. The CDA method can handle socioeconomic factors if they are included in the model formulation. However, the multicollinearity problem and the need for a very large amount of data make the use of CDA models very difficult. It is shown in this paper that the neural network (NN) method can be used to model the residential energy consumption with the inclusion of socioeconomic factors. The appliances, lighting, and cooling component of the NN based energy consumption model developed for the Canadian residential sector is presented here and the effects of some socioeconomic factors on the residential energy consumption are examined using the model.

Keywords: air-conditioning; appliance; lighting; modelling; neural networks; residential energy consumption; socioeconomic factors.

DOI: 10.1504/IJGEI.2003.003969

International Journal of Global Energy Issues, 2003 Vol.20 No.3, pp.302 - 315

Published online: 10 May 2004 *

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