| ID | 177166 |
| Title Proper | Wind turbine cost reduction |
| Other Title Information | a detailed bottom-up analysis of innovation drivers |
| Language | ENG |
| Author | Elia, A |
| Summary / Abstract (Note) | Wind energy technologies have seen a rapid decline in costs in the last two decades, but the drivers for these cost reductions are poorly understood. This paper addresses this knowledge gap by quantitatively investigating the drivers behind the cost reductions of onshore wind turbines between 2005 and 2017. Starting from a bottom-up cost model, the paper advances the methodology by identifying the techno-economic variables responsible for cost reductions of individual components (in $/kW) and linking them to drivers, specifically: learning by-deployment, learning-by-researching, supply-chain dynamics, and market dynamics. The analysis finds that changes in materials (copper, fiberglass, and iron), labour (employee productivity), legal and financial costs contributed over 30% to the cost reduction of wind turbine prices over the period 2005–2017. Moreover, learning-by-deployment was the most important innovation driver, being responsible for half of the cost reduction. The findings point to the importance of policies tailored to technology's stage of development. For onshore wind energy, which entered a mature phase in the period covered by this analysis, policy support for the needs of a growing industry such as stable support schemes together with appropriate regulatory and investment environments were more important than direct policy support for R&D which played a more important role in earlier periods. |
| `In' analytical Note | Energy Policy Vol.147; Dec 2020 : p. 111912 |
| Journal Source | Energy Policy 2020-12 147 |
| Key Words | Technology innovation ; Technology Learning ; Onshore Wind Technology ; Bottom-up Cost Model ; Innovation Drivers |