AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results

Rosenlieb, Evan; Levine, Aaron; Rivers, Marie; Phillips, Tyler B.; Hussain, Tanveer; Gallego-Calderon, Juan; Sun, Mucun

doi:10.25984/2499473

Title: AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results

Dataset
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Abstract

This dataset contains results of the technical potential analysis of floating photovoltaics (FPV) on federally owned or permitted reservoirs in the United States. Estimates of the area of reservoirs that is technically feasible for FPV development are provided for reservoirs that are owned by the US Army Corps of Engineers or the US Bureau of Reclamation, or are associated with hydropower dams licensed by the Federal Energy Regulatory Commission. Other associated data are included, such as estimates of the potential evaporative losses of FPV development, and whether the waterbody is associated with an energy community or disadvantaged community that could qualify it for investment or production tax credits. Data is provided both as a spreadsheet and in a geospatial format including the waterbody geometries. Please read the included readme for more detailed field definitions.

Authors:

;

; Rivers, Marie;

;

National Renewable Energy Lab

Publication Date:: Fri Nov 08 04:00:00 UTC 2024

Other Number(s):: 6234

Research Org.:: DOE Open Energy Data Initiative (OEDI); National Renewable Energy Lab

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office (EE-4S)

Collaborations:: National Renewable Energy Lab

Subject:: Array; FPV; Floating PV; Floating Solar; PV; United States; area; data; energy; evaporative loss; power; reservoirs

OSTI Identifier:: 2499473

DOI:: https://doi.org/10.25984/2499473

Citation Formats


                    Rosenlieb, Evan, Levine, Aaron, Rivers, Marie, Phillips, Tyler B., Hussain, Tanveer, Gallego-Calderon, Juan, and Sun, Mucun. AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results.  United States: N. p., 2024. 
        Web.  doi:10.25984/2499473.

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                    Rosenlieb, Evan, Levine, Aaron, Rivers, Marie, Phillips, Tyler B., Hussain, Tanveer, Gallego-Calderon, Juan, & Sun, Mucun. AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results.  United States.  doi:https://doi.org/10.25984/2499473

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                    Rosenlieb, Evan, Levine, Aaron, Rivers, Marie, Phillips, Tyler B., Hussain, Tanveer, Gallego-Calderon, Juan, and Sun, Mucun. 2024.  
"AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results".  United States.  doi:https://doi.org/10.25984/2499473.  https://www.osti.gov/servlets/purl/2499473. Pub date:Fri Nov 08 04:00:00 UTC 2024

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@article{osti_2499473,

  title        = {AquaPV: Foundational Analysis and Industry Guidance on Floating PV Results},

  author       = {Rosenlieb, Evan and Levine, Aaron and Rivers, Marie and Phillips, Tyler B. and Hussain, Tanveer and Gallego-Calderon, Juan and Sun, Mucun},

  abstractNote = {This dataset contains results of the technical potential analysis of floating photovoltaics (FPV) on federally owned or permitted reservoirs in the United States. Estimates of the area of reservoirs that is technically feasible for FPV development are provided for reservoirs that are owned by the US Army Corps of Engineers or the US Bureau of Reclamation, or are associated with hydropower dams licensed by the Federal Energy Regulatory Commission. Other associated data are included, such as estimates of the potential evaporative losses of FPV development, and whether the waterbody is associated with an energy community or disadvantaged community that could qualify it for investment or production tax credits. Data is provided both as a spreadsheet and in a geospatial format including the waterbody geometries. Please read the included readme for more detailed field definitions.},

  doi          = {10.25984/2499473},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Nov 08 04:00:00 UTC 2024},

  month        = {Fri Nov 08 04:00:00 UTC 2024}

}

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DOI: https://doi.org/10.25984/2499473

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