GL Garrad Hassan Updates Wind Farm Design Software

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To further boost the productivity of the wind farm design process, GL Garrad Hassan presented an updated version of its WindFarmer software at AWEA Windpower 2011. The software facilitates the layout of wind farms to maximize the power produced while minimizing the environmental impact. The new release of the software offers project planners and developers an even more powerful tool for wind farm design and energy yield calculations.

Users of Geographic Information System (GIS) systems benefit from WindFarmer 4.2 now supporting a wider range of Environmental Systems Research Institute (ESRI) Shape files, giving more options for importing object locations (turbines, houses, viewpoints, etc.), boundaries, and terrain contours. The new version provides developers with new tools for the design and optimization of regular turbine layouts, and improved modeling of array effects between large wind farms. The environmental engineer will find an updated shadow flicker analysis that uses map projection information to automatically detect longitude and latitude and True North-Grid North deviation. Met data analysts will benefit from its expanded MCP+ Module that provides more versatile data displays and analysis, for example allowing a choice of the number of direction sectors and the scaling of TAB files.

WindFarmer previously supported 10 languages—Chinese, English, German, Greek, French, Italian, Japanese, Spanish, Turkish, and Portuguese—to which the 4.2 release adds Arabic and Polish language versions. GL Garrad Hassan provides not only the software but training and technical support in all 12 languages.

Professionals around the world work with WindFarmer to design both onshore and offshore wind farms of all sizes. This software tool integrates wind farm energy and environmental assessments with wind farm layout design and data handling. It is acknowledged not only for its user-friendly interface and the speed and accuracy of its calculations, but also for the transparency of its data models. For more information visit www.gl-garradhassan.com/windfarmer.