State of the Art and Trends in Wind Resource Assessment

Abstract

Given the significant rise of the utilization of wind energy the accurate assessment of the wind potential is becoming increasingly important. Direct applications of wind assessment techniques include the creation of wind maps on a local scale (typically 5-20 km) and the micrositing of wind turbines, the estimation of vertical wind speed variations, prospecting on a regional scale (>100 km), estimation of the long-term wind resource at a given site, and forecasting. The measurement of wind speed and direction still widely relies on cup anemometers, though sonic anemometers are becoming increasingly popular. Moreover, remote sensing by Doppler techniques using the backscattering of either sonic beams (SODAR) or light (LIDAR) allowing for vertical profiling well beyond hub height are quickly moving into the mainstream. Local wind maps are based on the predicted modification of the regional wind flow pattern by the local atmospheric boundary layer which in turn depends on both topographic and roughness features and the measured wind rose obtained from one or several measurement towers within the boundaries of the planned development site. Initial models were based on linearized versions of the Navier-Stokes equations, whereas more recently full CFD models have been applied to wind farm micrositing. Linear models tend to perform well for terrain slopes lower than about 25% and have the advantage of short execution times. Long-term performance is frequently estimated from correlations with nearby reference stations with concurrent information and continuous time series over a period of at least 10 years. Simple methods consider only point-to-point linear correlations; more advanced methods like multiple regression techniques and methods based on the theory of distributions will be discussed. Both for early prospecting in regions where only scarce or unreliable reference OPEN ACCESSEnergies 2010, 3 1088 information is available, wind flow modeling on a larger scale (mesoscale) is becoming increasingly popular.

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

“…The selection of the wind farm location is commonly based on a hierarchy scheme including three general factors: (1) the available infrastructure (i.e., accounting for the current capacity of the electrical, civil engineering and communication infrastructure and its expansion plans); (2) the environmental suitability (e.g., accounting for restricted areas such as natural protected areas or bird conservation areas); and (3) the wind resource. The wind resource quantification [42][43][44][45] is based on long-term records (each record being a 10-min averaged measurement obtained from sampling with a frequency of 1 Hz or higher) of atmospheric variables exhibiting temporal and spatial variations: wind speeds [ , and sometimes even air quality. Since atmospheric variables are considered to be random on nature, further analyses are performed to study its statistical characteristics (e.g., determine its probability density functions), which allow the wind farm designer to quantify expected values at the potential wind farm site.…”

“…The output wind field is convoluted numerically with the resulting statistical distributions of the 10-min averaged wind speed measurements at different heights and wind directions, resulting in averaged wind resource maps at different heights, which are the base for the wind farm planning process. Other sources of information such as Mesoscale modeling and the Measure-Correlate-Predict (MCP) techniques [36,42] could also provide valuable information of the local atmospheric behavior and the wind resource potential.…”

Market Suitability and Performance Tradeoffs Offered by Commercial Wind Turbines across Differing Wind Regimes

“…Appreciable work has been done (and is ongoing) (i) to account for the variation of wind conditions at a particular site (e.g., wind distribution modeling [1,2]) and (ii) to address the intermittency of wind resources in the context of grid integration (e.g., energy storage technologies [3,4]). In contrast, there has been a limited amount of work that investigates the complex demands on wind turbine performance (when In this paper, we are particularly concerned with the role of the third factor in wind farm performance.…”

An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance

“…With the heavy dependence of local wind energy resources and grid connection, the development of a wind farm involves several important stages: early prospecting of suitable sites, wind mapping at the potential site and conceptual wind farm design, micro-siting of turbines and optimization, risk assessment, planning of certification towers, post-construction performance analysis, and operation [4]. In addition, a comprehensive evaluation of related factors, such as wind energy policy and economical feasibility, must also be carried out [3].…”