What’s Driven the Dramatic Technological Change in the US Wind Power Sector?

As the world’s major energy consumer and greenhouse gas emitter, the United States is striving to increase the share of renewable energy in its electricity supply so as to address climate change and energy security concerns. Among all renewable energy sources, wind energy has great potential to provide a significant share of electricity generation. During the last two decades, the United States has experienced tremendous technological change in wind power both in terms of cumulative installed capacity and generation performance of wind farms.  By the end of 2017, the cumulative wind installed capacity in the US was almost 35 times the total installed capacity in 2000. The share of wind power in total electricity supply increased from 0.77% in 2007 to 6.33% in 2017, which shows a significant divestment from fossil fuel energy in the power sector. With the development of larger wind turbines, better siting technologies, and improvement in power transmission, the average capacity factor[1] of wind farms in 2015 has become approximately 43% greater than the average performance of wind farms installed before 1998.

In a recent Energy Policy article, Dr. Tian Tang explains this immense technological progress in the US wind power industry from the perspectives of energy policies, technological learning, and collaboration in the power sector. She examines the installation and operation of all utility-scale wind farms between 2001 and 2012. She finds four major learning channels that have facilitated the performance improvement of US wind farms.

The first channel is through the R&D activities in the wind power equipment manufacturing (“learning-by-searching”). Through those R&D activities, larger wind turbines, higher hubs, more efficient turbine designs, improved control systems, and better forecasting technologies are made available to the market. With the advancement of wind turbine technologies, newer wind projects can select better wind technologies than wind farms installed previously, which significantly improve the performance across projects over time.

When a wind project comes to its operational stage, its performance is improved over time by gaining more operational experience (“learning-by-doing”) rather than technological advancement from wind turbine manufacturing. Empirical evidence shows that a wind farm’s capacity factor increases over time as the project operator accumulates more experience in wind farm installation and operation. In addition to learning by doing, a wind farm’s performance is also improved after more wind farms have been installed in the same state. This indicates the spillover effects of the wind farm operational experience. Wind farm operators may also learn how to operate wind farms more efficiently from their neighboring projects. Given the statewide knowledge spillovers regarding wind farm operation, it is justifiable to subsidize wind farm operators/owners to offset their incentives to wait and take advantages of other early adopters.  Otherwise, many potential investors (i.e. utilities) in wind power may wait to develop wind farms till the average performance of wind farms in a state reaches to a profitable level. Regarding different policy instruments to subsidize wind farms, this study finds that subsidies that are directly given to per kWh wind power generation (e.g. production tax credits) worked better than subsidies for wind farm installation (e.g. tax exemption or rebate for purchasing wind turbines).

Another important channel of learning is learning through collaboration among wind project participants (“learning-by interacting”). This study finds that a wind farm’s performance can be improved greatly when the wind farm operator has more collaborative experience with the same turbine manufacturer and the transmission system operator in previous wind projects, particularly when the transmission system is coordinated at the regional level. The regional collaboration can improve the integration of intermittent renewable resources like wind power through better forecasting wind generation at the regional level, information sharing, and resource pooling and mobilization.

[1] Capacity factor is the ratio of power actually produced by a wind farm in a given period to the potential output if it was operated at its full capacity. It is a commonly used measurement for wind farm performance.

Dr. Tian Tang is an assistant professor in the Askew School of Public Administration. This blog is based on her article, “Explaining Technological Change in the US Wind Industry: Energy Policies, Technological Learning, and Collaboration,” which appeared in Energy Policy in 2018. 


The featured image is from The Conversation.

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