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WIREs Energy Environ.
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Wind and solar resource data sets

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The range of resource data sets spans from static cartography showing the mean annual wind speed or solar irradiance across a region to high temporal and high spatial resolution products that provide detailed information at a potential wind or solar energy facility. These data sets are used to support continental‐scale, national, or regional renewable energy development; facilitate prospecting by developers; and enable grid integration studies. This review first provides an introduction to the wind and solar resource data sets, then provides an overview of the common methods used for their creation and validation. A brief history of wind and solar resource data sets is then presented, followed by areas for future research. WIREs Energy Environ 2018, 7:e276. doi: 10.1002/wene.276 This article is categorized under: Wind Power > Climate and Environment Solar Heating and Cooling > Climate and Environment Energy Infrastructure > Climate and Environment
Examples of solar and wind resource maps. (a) Annual average global horizontal irradiance (GHI) in India [Source: National Renewable Energy Laboratory (NREL), via http://openei.org]. (b) Monthly average wind speed for Gujarat, India (Source: NREL).
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U.S. annual average daily total global horizontal irradiance from the 1998–2015 NREL's National Solar Radiation Database data set.
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Example of the Global Wind Atlas, a recent wind climate calculation covering the globe with a spacing of 250 m. Interactive maps and analysis tools are available at http://globalwindatlas.com.
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Examples of the horizontal resolution shown on NREL's solar resource maps. (a) The annual average plane‐of‐array irradiance for 1985–1991 data at 40‐km horizontal resolution, produced in 2004. (b)The annual average plan‐of‐array irradiance for 1998–2005 at 10‐km resolution, produced in 2008. Source: NREL. For more details, see http://www.nrel.gov/gis/solar.html.
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U.S. annual average 100‐m wind speed for land and offshore. Source: NREL.
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U.S. annual average wind power from the 1986 National Wind Resource Map. Source: http://rredc.nrel.gov/wind/pubs/atlas/maps/chap2/2‐01m.html
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The WIND Toolkit web pages provide a graphical user interface to a large meteorological data and power data set.
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Locations of the National Oceanic and Atmospheric Administration (NOAA)‘s Surface Radiation, NREL, and Atmospheric Radiation Measurement sites in the United States. These sites provide the high‐quality data that are usually used to validate solar resource data sets.
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Examples of ground‐based measurement data used for resource modeling and validation. (a) a pyranometer near a solar energy facility in the United States (NREL 15537). (b) a buoy equipped with a wind lidar and other meteorological sensors (Source: Pacific Northwest National Laboratory via Flickr.)
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The process of producing the NSRDB data from satellite data, reanalysis data, and a radiative transfer model.
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The Wind Atlas Analysis and Application Program method: showing the analysis of an observed wind climate from a measurement site to produce a generalized wind climate (upward arrow) and the application of a generalized wind climate to produce a predicted wind climate at a turbine site (downward arrow). Reproduced with permission from the European Wind Atlas.
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Examples of the effect of horizontal resolution on apparent flow‐field variability over an area of 8750 m × 8750 m over flat terrain in Kansas during convective daytime conditions in the afternoon: (a) flow field using a mesoscale simulation with a 1250‐m grid spacing showing no variation in wind speed; (b) mesoscale flow downscaled with large eddy simulation on a 250‐m grid. Wind speed contours are 1 m/s, black lines denote grid cell boundaries.
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The downscaling process uses a combination of observational data sets, physical models, and transfer functions to estimate wind and solar resources at high temporal and spatial resolutions.
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