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Sengupta, M., Y. Xie, A. Lopez, A. Habte, G. Maclaurin, and J. Shelby. 2018. \"The National Solar Radiation Data Base (NSRDB).\" Renewable and Sustainable Energy Reviews 89 (June): 51-60.

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Values are reported in MWh. Learn More
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Annual Generation (MWh):
Distance to Transmission Line (m): {d_trans}
Distance to Substation (m): {d_sub}
Distance to Nearest Road (m): {d_road}

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"https://oe.oregonexplorer.info/externalcontent/metadata/CandidateProjectArea_SOLAR_SL1_meta.pdf" }, { "encodeUriReplacementValues": "Automatic", "iconUri": null, "target": "_blank", "text": "Download", "toolTip": null, "uri": "https://oe.oregonexplorer.info/externalcontent/spatialdatafordownload/Candidate_Project_Area_Resource_Potential_OR_20210405.zip" } ], "arcadeExpressions": [], "isDynamic": false, "dynamicDefinition": null, "themeSettings": [], "tileLevelLimits": [] }, { "id": "6", "name": "Estimated Annual Solar Utility-Scale Capacity Factor", "nativeID": "6", "displayName": "Estimated Annual Solar Utility-Scale Capacity Factor", "description": "This dataset provides indication of utility scale solar resource potential, in terms of quality and quantity, for the State of Oregon.

Values are reported in terms of estimated annual capacity factor, a measure of solar resource quality. Capacity factor indicates the amount of energy produced in a typical year, as a fraction of maximum possible energy, if the facility were producing at full nameplate capacity, for 100% of the hours of the year. For example, a 100 MW solar power plant with 21% capacity factor would generate 100 MW x 8760 hrs/yr x 21% = 183,960 MWh/yr.Learn More
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Sengupta, M., Y. Xie, A. Lopez, A. Habte, G. Maclaurin, and J. Shelby. 2018. \"The National Solar Radiation Data Base (NSRDB).\" Renewable and Sustainable Energy Reviews 89 (June): 51-60.

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Values are reported in MWh. Learn More
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Annual Generation (MWh):
Distance to Transmission Line (m): {d_trans}
Distance to Substation (m): {d_sub}
Distance to Nearest Road (m): {d_road}

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indication of wind resource potential, in terms of quality and quantity, for the State of Oregon.

Values are reported in terms of estimated annual capacity factor, a measure of wind resource quality. Capacity factor indicates the amount of energy produced in a typical year, as a fraction of maximum possible energy, if the facility were producing at full nameplate capacity, for 100% of the hours of the year. For example, a 100 MW wind power plant with 28% capacity factor would generate 100 MW x 8760 hrs/yr x 28% = 245,280 MWh/yr.
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Values are reported in terms of estimated annual capacity factor, a measure of wind resource quality. Capacity factor indicates the amount of energy produced in a typical year, as a fraction of maximum possible energy, if the facility were producing at full nameplate capacity, for 100% of the hours of the year. For example, a 100 MW wind power plant with 28% capacity factor would generate 100 MW x 8760 hrs/yr x 28% = 245,280 MWh/yr. Learn More
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Values are reported in MWh. Learn More
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Distance to Substation (m): {d_sub}
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Speed at 100-Meter above Surface Level", "description": "This data provides modeled annual average wind speed for the contiguous United States both onshore and offshore for the period 2007–2013. This dataset was derived from the WIND Toolkit. Citations: Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory. Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. \"The Wind Integration National Dataset (WIND) Toolkit.\" Applied Energy 151: 355366. Lieberman-Cribbin, W., C. Draxl, and A. Clifton. 2014. Guide to Using the WIND Toolkit Validation Code (Technical Report, NREL/TP-5000-62595). Golden, CO: National Renewable Energy Laboratory. King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory. Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. \"The Wind Integration National Dataset (WIND) Toolkit.\" Applied Energy 151: 355366. Lieberman-Cribbin, W., C. Draxl, and A. Clifton. 2014. Guide to Using the WIND Toolkit Validation Code (Technical Report, NREL/TP-5000-62595). Golden, CO: National Renewable Energy Laboratory. King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.

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This dataset contains information about the biomass resources generated by county in the United States. It includes the following feedstock categories: crop residues, forest residues, primary mill residues, secondary mill residues, and urban wood waste.
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The project estimated the naturally available and technically recoverable U.S. wave energy resources, using a 51-month Wavewatch III hindcast database developed especially for this study by National Oceanographic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction. For total resource estimation, wave power density in terms of kilowatts per meter is aggregated across a unit diameter circle. This approach is fully consistent with accepted global practice and includes the resource made available by the lateral transfer of wave energy along wave crests, which enables densities within a few kilometers of a linear array, even for fixed terminator devices.
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Wave energy period is a sea state parameter, derived from the zeroth and first negative moments of the frequency spectrum. It is the period corresponding to the weighted average of the wave energy.

The project estimated the naturally available and technically recoverable U.S. wave energy resources, using a 51-month Wavewatch III hindcast database developed especially for this study by National Oceanographic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction. For total resource estimation, wave power density in terms of kilowatts per meter is aggregated across a unit diameter circle. This approach is fully consistent with accepted global practice and includes the resource made available by the lateral transfer of wave energy along wave crests, which enables densities within a few kilometers of a linear array, even for fixed terminator devices.
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Significant wave height is a spectrally derived time-series, which is the average of the highest third of the waves in a random seaway and roughly corresponds to the mean wave height.

The project estimated the naturally available and technically recoverable U.S. wave energy resources, using a 51-month Wavewatch III hindcast database developed especially for this study by National Oceanographic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction. For total resource estimation, wave power density in terms of kilowatts per meter is aggregated across a unit diameter circle. This approach is fully consistent with accepted global practice and includes the resource made available by the lateral transfer of wave energy along wave crests, which enables densities within a few kilometers of a linear array, even for fixed terminator devices.
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January: {jan_ssh}
April: {apr_ssh}
October: {oct_ssh}
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