US Wind Research Articles

Spatial Processes of Industry Emergence: US Wind Turbine Manufacturing Industry

This research seeks to understand the underlying locational resources and dynamics explaining the location and growth of new, environmental technology industries. Beginning with the location patterns of the US wind turbine manufacturing industry, this research uses demand, supply and policy factors to explain how the resources and dynamics of a location help shape its future industrial composition. The findings include the prominent role of demand factors, including wind power resources, existing installed wind power and electricity prices as well as supply factors, but the weakness of the influence of governmental policy. This research can assist companies, investors and policy-makers understand the spatial dynamics of industry emergence in order to better align their strategies and policies.

“We Don’t Take the Pledge”: Environmentality and environmental skepticism at the epicenter of US wind energy development

This study analyzes pro-wind, “anti-environmental” discourses prevalent among key stakeholders in Nolan County, Texas, the epicenter of US wind power. We draw upon interviews conducted within a Q-method study to examine environmental views held by key actors in wind-farm development. We frame our analysis within the theoretical field that engages the formation of environmental subjects, defined as the process through which individuals and communities align their environmental practices with state ends. We argue that this is a process that can be incomplete or in tension with other subject positions, which together may lead to unexpected environmental views. We introduce “environmental skepticism,” defined as a rejection of ecological science steeped in deep anthropocentrism and possessive individualism, as a dominant counter-narrative informing certain environmental subjectivities. The remainder of the paper describes Texas wind stakeholders’ views or subject positions on energy and the environment and reveals how environmental skepticism is not overturned even as renewable energy supports the local economy. We analyze wind stakeholders’ environmental subjectivity in terms of emergent subject positions as “reflexive environmental skepticism,” a view that accepts the economic products, processes, and policy innovations advocated by ecological modernization without accepting the core claim that innovations are required to adapt to environmental change.

Resisting and Reconciling Big Wind: Middle Landscape Politics in the New American West

: While critical geographers have addressed how place politics impacts rural landscapes, less attention has been paid to the particular ways in which rural landscape identities are being impacted by the new energy economy. The nascent US wind energy opposition movement is evidence of broad, organized resistance to the landscape impacts associated with the re-sculpting of rural energy geographies. Drawing from cultural landscape and place theory, this article examines the shifting terrain of wind opposition in the “New American West”. The article argues that wind energy opposition is fundamentally about who speaks for and negotiates conflicting social commitments to technology, economic values and an imagined American pastoral identity. By examining a case study of wind development in Nevada, this article considers how renewable energy development can constructively acknowledge the important role the “middle landscape” continues to play in American constructions of rural space.

Full-scale validation of vortex suppression techniques for mitigation of roof uplift

Widespread damage to roofs in hurricanes and other high wind events has highlighted the need for improving the wind performance of roofs, including both new construction and retrofit on existing buildings. Effective and economical methods to mitigate wind effects on roof components are sought to reduce accumulated losses from frequently recurring low- and moderate-intensity events. An experimental study was carried out in the 6-fan Wall of Wind (WoW) testing apparatus to assess the effectiveness of aerodynamic edge devices at full scale in reducing wind effects over the roof corner and edge regions. Two sets of tests, roof gravel scour testing and pressure testing, were carried out to visualize the development of edge vortices and compare roof uplift pressures with and without aerodynamic edge shapes, thus allowing the estimation of the effects of such shapes in alleviating wind damage of roofing material as well as high uplift pressures on roofs. Probabilistic estimates of peak pressures indicated that the use of such mitigation devices resulted in significant reductions in uplift within the instrumented area, which according to the US wind load specifications (ASCE 7-05) represents a corner section of the roof that will experience the highest suction. The largest reduction was achieved with the Flat Roof AeroEdge Guard (FRAG1). This research demonstrates the potential for substantial reduction of roof uplift pressures through the development and application of mitigation techniques to lessen or prevent hurricane-induced damage to new and existing roofs.

Analysis: Component crunch

While business booms for the US wind industry, European cohorts struggle to source turbine parts.

A comparison of methods of extreme wind speed estimation

The paper presents a comparative assessment of methods for extreme value analysis of the US wind speed data using four different methods, namely Standard Gumbel, Modified Gumbel, Peaks-Over-Threshold (POT) and Method of Independent Storms (MIS). The analysis highlights the influence of methodological assumptions on the estimates of design wind speed corresponding to 50-year and 500-year return period. The results demonstrate that the MIS method leads to more stable quantile estimates than the POT method.

Generalized extreme gust wind speeds distributions

Since summer 1996, the US wind engineers are using the extreme gust (or 3-s gust) as the basic wind speed to quantify the destruction of extreme winds. In order to better understand these destructive wind forces, it is important to know the appropriate representations of these extreme gust wind speeds. Therefore, the purpose of this study is to determine the most suitable extreme value distributions for the annual extreme gust wind speeds recorded in large selected areas. To achieve this objective, we are using the generalized Pareto distribution as the diagnostic tool for determining the types of extreme gust wind speed distributions. The three-parameter generalized extreme value distribution function is, thus, reduced to either Type I Gumbel, Type II Frechet or Type III reverse Weibull distribution function for the annual extreme gust wind speeds recorded at a specific site. With the considerations of the quality and homogeneity of gust wind data collected at more than 750 weather stations throughout the United States, annual extreme gust wind speeds at selected 143 stations in the contiguous United States were used in the study.

An adaptive exponential model for extreme wind speed estimation

The peaks-over-threshold (POT) method is a useful alternative to classical annual-maxima method for the estimation of extreme wind speeds from limited historical data. The basic idea is to model peak wind speeds exceeding a high threshold by the Pareto distribution, which is their domain of attraction. However, practical applications of POT method are confounded by the indeterminate nature of correct threshold beyond which the Pareto model becomes effective. This difficulty is further compounded by acute threshold sensitivity of wind speed estimates, which can be attributed to erratic variation of model and sampling errors with selected threshold values. To improve the statistical accuracy and reduce the threshold sensitivity of POT estimates, the paper presents an adaptive exponential model that relies on a quantitative notion of uncertainty used in information theory. In the proposed approach, an exponential prior is assigned to suitably preconditioned data, and it is augmented with additional sample information in an optimal sense through the principle of Minimum Cross-Entropy (Cross-Ent). Novel features of this model are systematic minimization of model error and significant reduction in sampling error by the use of probability-weighted moments. The performance of the proposed approach is compared with widely used Pareto and exponential models. Simulation-based examples illustrate that Cross-Ent estimates of 50 and 1000-year quantiles are almost unbiased and insensitive to the threshold value. POT analyses of US wind speed data also reveal a remarkably stable trend of Cross-Ent estimates. Bootstrap simulations also confirm higher accuracy of the proposed method in comparison to other traditional methods.

Minimum cross-entropy method for extreme value estimation using peaks-over-threshold data

Extreme quantile estimation in the peaks-over-threshold (POT) method is based on the Pareto distribution model for peaks of a time series exceeding a high threshold. However, a major practical difficulty associated with this approach is the large and erratic variability of quantile estimates with respect to the threshold value, which is not known a priori. Recognizing the limited applicability of the Pareto model to a narrow and unidentifiable range of peak data, the paper presents a more general non-parametric probabilistic model to improve the statistical accuracy and of POT estimates. The proposed approach relies on a quantitative notion of uncertainty and the minimum cross-entropy principle (Cross-Ent), commonly used in information theory and signal analysis. The model combine a suitable prior distribution with sample estimates of probability-weighted-moments, which exhibit much smaller sampling uncertainty than estimates of ordinary moments. The performance of the Cross-Ent approach is compared with a widely used Pareto model of peak data and an exponential model of transformed data. Examples based on simulated data illustrate that Cross-Ent estimates of 50 and 1000-year quantiles are almost unbiased and insensitive to the threshold value. The analysis of US wind speed data also reveals a remarkably stable trend of Cross-Ent estimates with very limited threshold sensitivity, which is in clear contrast with rapidly fluctuating estimates obtained from the other two methods.

Wind and the US power crisis: Experiences of a wind power developer in the USA

The year 2000 saw the pace of growth for the US wind industry lapse following the hectic ventures of the 1999 wind rush. The US recorded little net growth. Of course, contracts were being signed for new projects to be built in 2001 but the year was generally one of consolidation and orientation before the next expected gauntlet of production tax credits (PTCs) were laid down. Then, the reintroduction of the PTCs, the mechanism of federal support, was far from certain. Gavin McAlpine, Renewable Energy Systems Ltd, UK describes the experiences and perspectives of a wind power developer in the USA.

The estimation of extreme quantiles of wind velocity using L-moments in the peaks-over-threshold approach

The paper evaluates the effectiveness of the method of L-moments for estimating parameters of the Pareto distribution model of peaks over a sufficiently high threshold, and compares its performance against a widely used method of de Haan (de Haan L. Extreme value statistics. In: Galambos J, Lechner J, Simin E, editor. Extreme value theory and applications, vol. 1. 1994. p. 93–122). Monte Carlo simulations and actual wind speed data collected at various stations in the United States have been utilized in this study. In the de Haan method, the first two moments of peaks of log-transformed data are used for the parameter estimation, whereas the L-moment method utilizes linear combinations of expectations of order statistics of peaks in the original data. Despite the procedural differences, the paper shows that the de Haan and two L-moments based estimates of the tail shape parameter are in fairly close agreement in simulated data as well as in the US wind speed data. Furthermore, higher order estimates of the shape parameter are obtained using the L-skewness of peaks data. Such estimates appear to provide a more stable upper bound, which can be useful in identifying meaningful values of design quantiles.

Plans for US wind tunnel set to take off

Plans for US wind tunnel set to take off

A Fair Wind Blows for One Green Technology

The newest windmills are small and robust, typically capable of generating 50 to 500 kilowatts each. Sales have been helped along, both in Europe and the United States, by laws requiring utility companies to offer fixed purchase-price contracts to suppliers of wind electricity. Another boost comes from the National Energy Policy Act, signed into law last fall by George Bush. It permits a 1.5 cent per kilowatt-hour tax credit for generators of electricity from renewable sources. Emphasizing energy production is [open quotes]a much smarter approach[close quotes] than just rewarding construction of new windmills, says Alexander Ellis, an executive at Kenetech/US Windpower, because it encourages companies to deliver durable products. Today, the wind energy business seems to be booming, bearing out the Administration's faith that environmental technologies can open new markets. There are now more than 16,000 wind turbines installed in the United States, according to DeMeo, most of them still in California. Europe is also moving ahead. Although European countries have installed fewer machines to date, DeMeo says, the European Community has ambitious plans, calling for double the current US wind energy capacity by the end of the decade. About 10 major manufacturers in the United States and abroad aremore » vying for this business. It took some fine-tuning, but government incentives to nurture this green technology seem to be working.« less