Elsevier

Energy Policy

Volume 42, March 2012, Pages 628-641
Energy Policy

Understanding wind turbine price trends in the U.S. over the past decade

https://doi.org/10.1016/j.enpol.2011.12.036Get rights and content

Abstract

On a $/kW basis, wind turbine prices in the U.S. have declined by nearly one-third on average since 2008, after having previously doubled over the period from 2002 through 2008. These two substantial and opposing trends over the past decade – and particularly the earlier price doubling – run counter to the smooth, gradually declining cost trajectories predicted by standard learning curve theory. Taking a bottom-up approach, we examine seven possible drivers of wind turbine prices in the U.S., with the goal of estimating the degree to which each contributed to the doubling in turbine prices from 2002 through 2008, as well as the subsequent decline in prices through 2010. In aggregate, these seven drivers – which include changes in labor costs, warranty provisions, manufacturer profitability, turbine scaling, raw materials prices, energy prices, and foreign exchange rates – explain from 70% to 90% (depending on the year) of empirically observed wind turbine price movements in the U.S. through 2010. Turbine scaling is found to have been the largest single contributor to the price doubling through 2008, although the incremental cost of scaling has been justified by greater energy capture, resulting in a lower cost of wind generation.

Highlights

► Having doubled from 2002 to 2008, wind turbine prices have since fallen by one-third. ► We analyze seven potential drivers of wind turbine prices over the past decade. ► Turbine scaling has had the largest influence, followed by weakness in the dollar. ► Changes in the price of energy inputs had the smallest impact.

Introduction

A considerable literature has developed using learning curve theory to explore how increases in cumulative wind power capacity (and other factors) have historically driven down wind energy costs (for a brief survey of the peer-reviewed literature, see Wiser et al., 2011a). The principal parameter calculated by these studies is the learning rate: for every doubling in cumulative production or installation, the learning rate specifies the associated percentage reduction in costs. Learning rates based on historical data are then often used to forecast future cost developments. As an example, Wiser and Bolinger (2011) calculate a learning rate of 14.4% for the installed cost of wind power projects in the United States during the period between 1982 and 2004, meaning that for each doubling in cumulative installed wind capacity worldwide over this period, installed wind project costs in the U.S. fell by 14.4% on average.

These historical cost reductions, in concert with governmental policies and other drivers, helped to fuel rapid growth in the industry, both domestically and abroad, starting around the turn of the century (Fig. 1). In fact, although wind power technology has been commercially available for decades, more than 90% of all wind power capacity both in the U.S. and worldwide has been installed in just the last 10 years. Over this period, global installed wind power capacity more-than-doubled in the four years from 2002 through 2005, and then again in the three years from 2006 through 2008; it is currently on track to double yet again by late 2011.

Consistent with standard learning curve theory, the most-recent doubling expected by late 2011 has, in fact, been accompanied by significant cost reductions: as demonstrated later in Section 2, wind turbine prices in the U.S. have fallen somewhere on the order of 20–33% on average since 2008. By some accounts, these turbine price declines, in combination with improvements in turbine design and performance, will result in a lower cost of wind electricity among projects currently being built than has ever before been possible (Wiser et al., 2011b).

It is important to recognize, however, that the substantial turbine price declines since 2008 started from elevated levels that, themselves, were not consistent with a simple understanding of standard learning curve theory. Rather than the nearly 30% decline in wind project costs that learning curve theory would have expected from 2002 through 2008 as a result of the two doublings in global installed capacity over this period, reported wind project costs in the U.S. actually increased by more than 50% percent over this period (Wiser and Bolinger, 2011), due primarily to a doubling in wind turbine prices. This doubling in wind turbine prices through 2008 marks a substantial divergence from the simple application of learning curves to cumulative wind power installations.

This divergence has important implications for the wind industry, policymakers, research and development (R&D) program managers, and energy analysts. With the wind industry only recently becoming a serious contributor to the power sector in the U.S. and globally, it must take care that unexpected cost inflation does not price wind out of the market, leading to demand destruction. Policymakers who count on wind to provide a growing share of the world's electricity needs – and who enact policies aimed to achieve that goal – want reassurances that wind can meet this challenge in a cost-effective manner (and perhaps even eventually wean itself off of direct public policy support altogether). R&D managers need to understand past cost trends in order to target future research most effectively. Finally, energy analysts who have heretofore placed some faith in the simple application of learning curves to project future technology costs must potentially reevaluate their beliefs and develop a more nuanced understanding of the drivers of wind (and other forms of) power costs.

Common to all four sets of stakeholders is a growing need to understand what specific factors – if not learning effects – have been driving recent wind power cost trends, and in particular the doubling in wind turbine prices from 2002 through 2008. This article seeks to contribute to such an understanding, with a specific focus on the cost of wind turbines deployed onshore in the United States. In doing so, it builds on the work of other studies that have begun to develop a deeper understanding of historical renewable energy cost drivers beyond simple, traditional concepts of learning (see, e.g., Ferioli et al., 2009, Nemet, 2006, Papineau, 2006, Yu et al., 2011),1 as well as those that have examined in some detail other causal influences to wind power costs, both on- and offshore (e.g., Berry, 2009, Blanco and Isabel, 2009, Bolinger and Wiser, 2009, BWEA & Garrad Hassan, 2009, Carbon Trust, 2008, Dinica, 2011, Ernst & Young, 2009, Greenacre et al., 2010, Milborrow, 2008, Willow and Valpy, 2011).2

To set the stage, Section 2 documents the increase in onshore wind turbine prices from 2002 through 2008 and the subsequent decline through 2010 using empirical data from the United States, as well as data provided by Vestas—the second-largest wind turbine supplier in the U.S. market over this period. Section 3 examines seven different drivers that have been implicated to varying degrees in the run-up in wind turbine prices through 2008. Based on the analysis in Section 3, Section 4 presents the approximate degree to which each of these seven drivers, both individually and in aggregate, is found to have contributed to the overall movement in wind turbine prices over this period. Section 5 concludes by drawing insights from the analysis, and using them to look ahead to 2011 and beyond.

Before proceeding, we emphasize that this article focuses solely on wind turbine prices, rather than on the total installed cost of wind projects (which also includes balance of plant costs) or on the levelized cost of wind generation (which is further affected by financing terms, operating and maintenance expenses, and the amount of electricity generated). For the purposes of this article, a wind turbine's price is assumed to cover the tower, nacelle (and all of the components therein, such as the generator), and a rotor with blades, all delivered to the project site—foundations and other balance of plant work are not considered to be included in a turbine's price. In general, wind turbine prices account for roughly 60–70% of total installed project costs, and a slightly lower percentage of the levelized cost of wind generation (due to the latter also reflecting O&M and financing costs). Though it is ultimately the levelized cost of generation that is the most important of these three cost metrics, understanding trends in wind turbine pricing is a critical element to understanding trends in the levelized cost of wind generation.

Section snippets

Wind turbine price trends in the United States

Berkeley Lab has gathered price data on 81 U.S. wind turbine transactions totaling 23,850 MW announced from 1997 through early 2011. Because of limitations in the data sources – most of which are press releases and news reports – the precise content of many of the individual turbine transactions is not known, though most transactions likely include only the turbines and towers delivered to the project site, as well as limited warranty and service agreements. Balance of plant (“BOP”)

Wind turbine price drivers

Taking a bottom-up approach, this section examines seven potential drivers of wind turbine prices in the United States, with the goal of estimating the degree to which each contributed to the increase in turbine prices from 2002 through 2008, as well as the subsequent decline in prices through 2010; continued turbine price reductions experienced in the first half of 2011 are addressed to only a limited extent, in Section 5.7

Aggregate impact of turbine price drivers

The individual impacts of each of the seven drivers of wind turbine prices examined in 3.1 Labor costs, 3.2 Warranty provisions, 3.3 Turbine manufacturer profitability, 3.4 Increasing turbine size and energy capture, 3.5 Raw materials prices, 3.6 Energy prices, 3.7 Foreign exchange rates are summarized in Table 5. To focus attention on the overall trends, the table presents cumulative impacts over the two periods of major turbine price movements in the past decade—i.e., the doubling in turbine

Looking ahead

The analysis described in Section 3, with results summarized and discussed in Section 4, extends through 2010. At the time of writing, however, three quarters of 2011 have already passed, begging the question of how turbine prices have moved so far in 2011 and how the drivers highlighted in this article have been impacting those prices. Vestas (2011d) reports that Vestas' average (nominal) price on new orders worldwide during the first half of 2011 was 967 EUR/kW, down 2.5% from 992 EUR/kW in

Acknowledgments

The work described in this article was funded by the U.S. Department of Energy's Wind & Water Power Program, within the Office of Energy Efficiency and Renewable Energy, under Contract no. DE-AC02-05CH11231.

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