Wind energy is a clean, renewable energy source with low operating costs and zero emissions. Innovation in the wind energy sector applies to any onshore wind turbine that is more cost-effective than previous versions, and the main source of cost reduction is the size of the wind turbines. However, noninnovative forces such as interest rates, material prices, exchange rates, and wind speed fluctuations affect the production costs of wind energy, and until now, experts have not managed to control for these noninnovative forces.
Researcher Dali T. Laxton conducted a learning curve analysis that measures the correlation between the deployment of wind energy technology and electricity production cost reduction. Laxton’s study, published in the Journal of Energy Engineering, explains wind technology production cost reduction trends through changes in the technical parameters of wind turbines. The method outlined in the paper “Novel Measure of Innovation: Application to the Onshore Wind Energy Sector in the US” effectively controls for the noninnovative determinants of the production cost and supports the breakdown of these costs to identify the drivers of innovation. Read the full paper at https://doi.org/10.1061/(ASCE)EY.1943-7897.0000838. The abstract is below.
When technological innovations are implemented in the wind energy sector, one should observe reductions in the production cost of electricity. However, the accuracy of inferring the rate of innovation from production cost reductions is open to challenge when those costs change due to factors not attributable to technological innovation. To control for such factors, this study applies engineering models and derives production cost reduction trends through changes in the technical parameters of wind turbines. The obtained innovation measure is unlikely to be affected by the noninnovative determinants of the production cost as long as the underlying engineering models are accurate. The usefulness of the generated innovation measure is illustrated in the context of learning curve literature.
The ASCE Library has the complete paper: https://doi.org/10.1061/(ASCE)EY.1943-7897.0000838