Title: Learning-by-doing on both the demand and the supply sides: implications for electric utility investments in a Heuristic model

Authors: John A. ''Skip'' Laitner, Alan H. Sanstad

Addresses: EPA Office of Atmospheric Programs, 1200 Pennsylvania Avenue NW, MS 6201-J, Washington, DC 20460, USA. ' Lawrence Berkeley National Laboratory, #1 Cyclotron Road, MS 90-4000 Berkeley, CA 94720, USA

Abstract: As new technologies enter the marketplace, and as experience is gained in both their production and use, costs tend to decline with each successive doubling of investment or production. A number of studies have indicated that the effects of including learning-by-doing in energy forecasting and simulation modelling may be substantial relative to modelling with only ||autonomous|| or ||exogenous|| technical change. However, these studies have focused almost exclusively on supply-side technologies. This paper instead examines learning-by-doing for demand-side technologies. Omitting the learning-by-doing demand-side perspective may introduce a bias into technology forecasts. We explore the implications of this observation through the application of a heuristic model that captures the anticipated electricity service demand within USA over the next 30 years. We examine how including demand as well as supply-side learning could impact technology investment patterns within the US electric utility industry.

Keywords: learning-by-doing; demand-side technologies; forecast bias; electricity demand; technology investment.

DOI: 10.1504/IJETP.2004.004592

International Journal of Energy Technology and Policy, 2004 Vol.2 No.1/2, pp.142 - 152

Published online: 26 May 2004 *

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