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Abstract:
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Escalating concerns over energy security, the reliability of national electricity grids, and the environmental consequences associated with burning fossil fuels, among other things, have led to calls for policies that increase national reliance on renewable energy. As such, renewable technologies, especially wind energy have garnered significant attention in recent years. Wind energy represents one of the fastest growing energy sources, and a carbon-free alternative to traditional fossil fuel based technologies. The cost-competitiveness of wind power relative to more conventional forms of power generation such as coal and natural gas constitutes a significant concern in the wind industry. In order for renewable technologies such as wind to gain market share, innovations that lead to cost reductions must exist. Since the mid-1970's, considerable progress has been made in the development of wind turbines for electric generation. In conjunction with technological improvements, the cost of electricity from utility-scale wind systems has dropped by more than 80 percent since the early 1980's. Despite these dramatic cost reductions, the cost of wind energy still constitutes a barrier to further development in many instances. Technological learning constitutes a basis for the justification of policy intervention that increases the market share of renewable technologies. Technological learning refers to the phenomenon that the cost of a technology decreases as the cumulative installation of the technology increases. The learning curve framework constitutes a means for evaluating the relative effectiveness of cost-reducing factors, and can help gauge the appropriate structure of policy support for developing technologies such as wind. This study utilizes a two-factor learning curve, based on data from the United States, Germany, Denmark, Spain, and the United Kingdom to calculate a learning by doing rate associated with wind energy capacity expansion, and a learning by searching rate associated with pubic wind R&D expenditures. The results suggest that policies aimed at capacity expansion, namely subsidies, tax credits, capacity mandates, or national targets, have been very effective at bringing down the cost of wind energy. The results also show that R&D support for wind energy is very important for driving cost reductions given a somewhat sustained commitment to R&D funding that continuously raises a country's R&D based knowledge stock. |