Explaining learning curves for wind power
Introduction
Concern about the environmental effects of fossil fuels and the fact that these resources are non-renewable have forced governments to draw attention to alternative energy sources, sources that are both more environment friendly and renewable. One of these sources is wind. Utilising the energy content in the wind is, basically, a very old energy technology, but only in the last decades has it become a potentially commercial energy source. The utilisation of wind energy differs greatly between countries, both due to different aerodynamic conditions and to differing policies.
During the last half of the 1990s, wind power has become the fastest growing energy technology in the world, with an average annual growth rate of nearly 28 per cent during 1995–1998 (AWEA, 2000). 1999 was the best year ever for wind energy with an increase in total installed capacity of 37 per cent, from 9800 to 13,400 MW. The growth rate in 2000 was slightly lower, down to 26 per cent, which was largely due to a dip in the US market (AWEA, 2001). By the end of 2000, total installed capacity was approximately 17,000 MW, enough to generate approximately 34 TWh of electricity.
In this article learning curves for wind power in three countries, Denmark, Germany and the United Kingdom, are compared. A learning curve shows the empirical relationship between costs and accumulated production or capacity. I discuss why these curves differ, and whether different policy measures play a significant role. By combining an analysis of learning curves with an analysis of policy programmes, the aim is to discover important factors that determine the slope of the curve. The result from this analysis might prove useful when designing measures in order to promote new technologies, as for instance wind power.
There are a lot of technological studies of learning curves for renewable energy sources, for instance Neij (1997), Neij (1999), Mattsson (1997) and McDonald and Schrattenholzer (2001). These typically discuss how the costs have been reduced over time, whereas our question is why the costs have been reduced. There are also a lot of studies concerning technology policies, and how to promote renewable energy sources, like Grubb (1997) and Jacobsson and Johnson (2000). But analyses like this, where one tries to reveal how technology and other policies affect the learning curve, are not to our knowledge common. Cory et al. (1999) analyse the role of R&D spending for cost reductions in wind turbines, a topic that is closely related to our analysis.
The discussion in the paper rests on empirical evidence from the countries chosen. But before turning to the empirical studies, we will address on a more theoretical basis, the issue of learning in development and production, illustrated by learning curves.
Section 3 accesses the historical development of wind power in the three countries; Denmark, Germany and the United Kingdom. These countries have used different regimes and combinations of measures. Moreover, the results, when it comes to cost per kW h installed and the amount of power generated have varied between them.
In Section 4, learning curves for the three countries are estimated and compared. The underlying factors that explain the shape and slope of the learning curve are being qualitatively discussed.
Section 5 includes the conclusions from the analysis, and some issues that ought to be considered when designing policies for renewable energy sources.
Section snippets
Learning curves
Learning, which is an important component in technological development, is often described in the form of learning curves. Such a curve shows the decline in costs of production as experience, and thereby learning, is gained. Performance will improve or costs will decline as one learns from actual production. The learning curve is an empirical operationalisation without any thorough theoretical foundation. The basic idea is that the more one engages in development, the more opportunities exist
Development of wind power
As an empirical example of the development cycle for a technology and different measures used to affect this development, we will discuss the utilisation of wind energy in different countries. There are several countries that have built a relatively substantial wind-energy industry since the 1980s, but here we restrict our study to three of them: Denmark, Germany, and United Kingdom. The innovation and diffusion characteristics have varied between these countries. These differences give us a
Learning curves for wind power
Based on the data about average cost per produced kW h and cumulative capacity, we have constructed learning curves for the three chosen countries. The elasticity parameter α has been estimated by applying least squares regression on the logarithmic form of Eq. (1)where b is freely estimated but can be considered as an estimate for c1.
As mentioned above, there is no single price or cost for wind generated electricity, and this aspect together with the fact that cost
Conclusions
Our study of factors behind the learning curve for utilisation of wind power in Denmark, Germany and United Kingdom suggests that policies that enhance the competition between generators can promote cost reductions. But on the other hand, too extensive competition actually may hamper the diffusion, as has been the case of United Kingdom. Through different forms of REFITs, Germany and Denmark has created more stable market conditions for wind-turbine owners, and this clearly has increased the
Acknowledgements
The author likes to thank Haakon Vennemo, Einar Bowitz, Andrew Ellis and an anonymous referee for comments on earlier drafts of this article. She also gratefully acknowledges the economic support provided by the Norwegian Research Council through the SAMRAM programme.
References (26)
Technologies, energy systems and the timing of CO2 emissions abatement
Energy Policy
(1997)- et al.
The diffusion of renewable energy technologyan analytical framework and key issues for research
Energy Policy
(2000) - et al.
Learning rates for energy technologies
Energy Policy
(2001) Use of experience curves to analyse the prospects for diffusion and adaption of renewable energy technology
Energy Policy
(1997)Cost dynamics of wind power
Energy
(1999)- AWEA, 2000. 1999 global wind energy market report. American Wind Energy Association, downloaded from...
- AWEA, 2001. 2000 global wind energy market report. American Wind Energy Association, downloaded from...
- BCG, 1973. The experience curve reviewed—II. History. Perspectives...
The Practice of EconometricsClassic and Contemporary
(1991)- BTM Consult, 1996. Kostpris-udviklingen på en kWh fra en vindmølle 1981–1995 (The development in cost-price for one kWh...
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