We also want to thank the NREL contributors and reviewers, including Eric Lantz, Paul Veers and Brian Smith, as well as Tiffany Byrne, who coordinated the project schedule and deliverables. Technical editing was provided by Deanna Cook and Sheri Anstedt.

No abstract

Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free via www.OSTI.gov.

Monin-Obukhov similarity theory (MOST) is commonly used to model the windspeed profile at altitudes relevant to wind-power production (e.g. 10-200 m). Though reasonably accurate for unstable to weakly stable stratification, this approach becomes less accurate under increasingly stable stratification, largely due to the constant-flux surface layer assumed by MOST becoming shallower than the altitude range of interest. Furthermore, above the surface layer, the Coriolis force has a considerable influence on the wind-speed profile (in particular in the formation of low-level jets) that cannot be modelled using similarity theory. Our goal is to compare the accuracy of alternative extrapolation models that are more physically appropriate above the surface layer. Using data from the 213-m Cabauw meteorological tower in the Netherlands between July 2007 and June 2008, it is shown that MOST is accurate only at low altitudes and low stability, and breaks down at high altitudes and high stability.Local similarity is generally more accurate than MOST across all altitudes and stabilities, though the model requires turbulent flux data at multiple altitudes that is generally impractical. In contrast, a two-layer MOST-Ekman model is found to be comparable to the other models at low stability ranges and considerably more accurate in the high stability range, while requiring only a measure of surface stability and the geostrophic wind.

Purpose Over the past two decades, energy efficiency of building operation has increased significantly. As a result, the percentage of building life cycle energy attributed to embodied energy has also risen. This percentage, as measured in recent LCA studies, ranges between 2% and 51% and is influenced by the different climatic, infrastructure, and building characteristics that comprise the input data for these studies. Comparing the results of these studies is helpful in understanding how different combinations of these characteristics influence the relative proportions of embodied and operational energy. However, results are also influenced by the subjectivity inherent in each LCA study. Thus, meaningful comparison of results requires documentation of study methodologies, as outlined in ISO 14041.