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

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