A Review of Factors Influencing the Cost Development of Electricity Generation Technologies

Abstract

This article reviews the literature on the past cost dynamics of various renewable, fossil fuel and nuclear electricity generation technologies. It identifies 10 different factors which have played key roles in influencing past cost developments according to the literature. These 10 factors are: deployment-induced learning, research, development and demonstration (RD&D)-induced learning, knowledge spillovers from other technologies, upsizing, economies of manufacturing scale, economies of project scale, changes in material and labour costs, changes in fuel costs, regulatory changes, and limits to the availability of suitable sites. The article summarises the relevant literature findings for each of these 10 factors and provides an overview indicating which factors have impacted on which generation technologies. The article also discusses the insights gained from the review for a better understanding of possible future cost developments of electricity generation technologies. Finally, future research needs, which may support a better understanding of past and future cost developments, are identified.

The experience curve theory and its application in the field of electricity generation technologies – A literature review

“…For example, learning through research and development or spillover effects from other industries are difficult to reliably quantify. Furthermore, experience and other factors explaining cost changes often show high levels of multicollinearity, making it difficult to distinguish between the effects of experience and the other factors [40][41][42][43].…”

“…Many academics point out that a number of other factors have been found to play significant roles in influencing technology cost developments, but these are not explicitly taken into account in experience curve analysis [for example 10]. These other factors notably include [43]: One-factor experience curves not only fail to appreciate these factors' respective roles in technology cost developments, but can also lead to omitted variable bias, i.e. the overestimation of the relevance of experience in reducing technology costs (as well as by the learning rates derived from these curves).…”

“…This section provides estimates of future one-factor learning rates for electricity generation technologies. The estimates are based on the findings from the literature review of historic learning rates discussed in Section 3, as well as on the findings from a complementary literature review [43] which looked at factors beyond experience that affect these technologies' costs. "Best guess" estimates for the future learning rates of individual technologies are provided.…”

“…Despite the apparent relevance of experience to the development of renewable and fossil fuel technology costs, the literature review has also shown that additional factors may play a considerable role [see also 43]. Commodity price fluctuations, for example, have had a significant influence since the mid-2000s, especially on wind turbine costs.…”

Applying Endogenous Learning Models in Energy System Optimization

“…These costs are especially important for renewable energy technologies, as their cost of electricity is dominated by the capital costs and are not affected by fossil fuel prices. Samadi [6] provides a broad overview of the factors that typically influence the costs of electricity generation. He groups these into four main clusters: learning and technological improvements, economies of scale, changes in input factor prices, and social and geographical factors.…”