Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth
This dataset contains global onshore and offshore wind supply curves based on a resource assessment performed at the National Renewable Energy Laboratory (NREL) based on the National Center for Atmospheric Research's (NCAR) Climate Four Dimensional Data Assimilation (CFDDA) mesoscale climate database. This overview is intended to provide a brief description of the origin of the tables in this workbook, not to fully explain the assumptions and calculations involved. The paper linked below includes full detail of sources and assumptions.
The supply curves are defined by country and resource quality. Onshore supply curves are further differentiated by distance to nearest large load or power plant, and offshore by distance to shore and water depth.
The CFDDA database contains hourly wind velocity vectors at a 40km grid, at multiple heights above ground level. For each grid cell, we create hourly wind speed distributions at 90m hub heights, and we compute gross capacity factor through convolution with a representative power curve. Output is derated for outages and wake losses to obtain net capacity factor. Onshore, we assumed a composite IEC Class II turbine; offshore, an IEC Class I turbine. We assumed a wind turbine density of 5 MW/km.
Land and sea area are characterized by country (or country-like object, e.g, Alaska), land use/land cover, elevation, and protection status. Protected, urban, and high-elevation areas are fully excluded, and certain land cover types are fractionally excluded. Offshore, area within 5 nautical miles of or farther than 100 nautical miles from shore are excluded, as are protected marine areas. Marine areas are assigned to country based on exclusive economic zones; unassigned or disputed areas are excluded.
As alluded to previously, in this workbook, "United States of America" refers only to the continental U.S. Alaska and Hawaii are counted separately because of their remoteness. Unassigned "countries" comprise relatively remote, unpopulated areas (Alaska, Greenland, remote islands); and disputed marine areas. We recommend that their resource remain unassigned rather than grouped into larger IAM regions.
Citation Formats
National Renewable Energy Laboratory. (2014). Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth [data set]. Retrieved from https://data.openei.org/submissions/273.
Sullivan, Patrick, Eurek, Kelly, Gleason, Michaek, Hettinger, Dylan, Heimiller, Donna, and Lopez, Anthony. Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth. United States: N.p., 25 Nov, 2014. Web. https://data.openei.org/submissions/273.
Sullivan, Patrick, Eurek, Kelly, Gleason, Michaek, Hettinger, Dylan, Heimiller, Donna, & Lopez, Anthony. Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth. United States. https://data.openei.org/submissions/273
Sullivan, Patrick, Eurek, Kelly, Gleason, Michaek, Hettinger, Dylan, Heimiller, Donna, and Lopez, Anthony. 2014. "Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth". United States. https://data.openei.org/submissions/273.
@div{oedi_273, title = {Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth}, author = {Sullivan, Patrick, Eurek, Kelly, Gleason, Michaek, Hettinger, Dylan, Heimiller, Donna, and Lopez, Anthony.}, abstractNote = {This dataset contains global onshore and offshore wind supply curves based on a resource assessment performed at the National Renewable Energy Laboratory (NREL) based on the National Center for Atmospheric Research's (NCAR) Climate Four Dimensional Data Assimilation (CFDDA) mesoscale climate database. This overview is intended to provide a brief description of the origin of the tables in this workbook, not to fully explain the assumptions and calculations involved. The paper linked below includes full detail of sources and assumptions.
The supply curves are defined by country and resource quality. Onshore supply curves are further differentiated by distance to nearest large load or power plant, and offshore by distance to shore and water depth.
The CFDDA database contains hourly wind velocity vectors at a 40km grid, at multiple heights above ground level. For each grid cell, we create hourly wind speed distributions at 90m hub heights, and we compute gross capacity factor through convolution with a representative power curve. Output is derated for outages and wake losses to obtain net capacity factor. Onshore, we assumed a composite IEC Class II turbine; offshore, an IEC Class I turbine. We assumed a wind turbine density of 5 MW/km.
Land and sea area are characterized by country (or country-like object, e.g, Alaska), land use/land cover, elevation, and protection status. Protected, urban, and high-elevation areas are fully excluded, and certain land cover types are fractionally excluded. Offshore, area within 5 nautical miles of or farther than 100 nautical miles from shore are excluded, as are protected marine areas. Marine areas are assigned to country based on exclusive economic zones; unassigned or disputed areas are excluded.
As alluded to previously, in this workbook, "United States of America" refers only to the continental U.S. Alaska and Hawaii are counted separately because of their remoteness. Unassigned "countries" comprise relatively remote, unpopulated areas (Alaska, Greenland, remote islands); and disputed marine areas. We recommend that their resource remain unassigned rather than grouped into larger IAM regions.
}, doi = {}, url = {https://data.openei.org/submissions/273}, journal = {}, number = , volume = , place = {United States}, year = {2014}, month = {11}}
Details
Data from Nov 25, 2014
Last updated Oct 1, 2024
Submitted Nov 25, 2014
Organization
National Renewable Energy Laboratory
Contact
Donna Heimiller