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5 results for “hydropower projects”
CONUS-wide Balancing Authority Scale Hydropower Projections derived from 9505 Third Assessment
<p>This dataset provides historical and climate projection monthly hydropower generation timeseries for balancing authorities within the contiguous U.S. (CONUS). These data were developed as an extension to the Department of Energy Water Power Technologies Office's SECURE Water Act Section 9505 Third Assessment (9505) and include both federal and non-federal hydropower facilities. Additional modeling detail can be found in <a href="https://iopscience.iop.org/article/10.1088/1748-9326/ad6ceb" target="_blank" rel="noopener">Broman et al., 2024</a> and in the article's <a href="https://github.com/9505-PNNL/broman-etal_2024_erl">metarepository</a>. </p> <p>The dataset is provided in three separate formats to facilitate ease of use:</p> <p>1) Machine-readable csv in 'tidy' data format:</p> <table> <tbody> <tr> <td><strong>Short Name</strong></td> <td><strong>Unit</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>class</td> <td>N/A</td> <td>simulation type; control: historical, cc: climate scenario</td> </tr> <tr> <td>forcing</td> <td>N/A</td> <td>meteorological forcing used to drive hydrology model</td> </tr> <tr> <td>model</td> <td>N/A</td> <td>hydrology model</td> </tr> <tr> <td>hp</td> <td>N/A</td> <td>hydropower model</td> </tr> <tr> <td>gcm*</td> <td>N/A</td> <td>global climate model name</td> </tr> <tr> <td>ds*</td> <td>N/A</td> <td>downscaling method; DBCCA (statistical), RegCM (dynamical)</td> </tr> <tr> <td>balancing_authority</td> <td>N/A</td> <td>balancing authority code</td> </tr> <tr> <td>year</td> <td>N/A</td> <td>year</td> </tr> <tr> <td>month</td> <td>N/A</td> <td>month</td> </tr> <tr> <td>modeled_generation_MWh</td> <td>MWh per month</td> <td>simulated generation</td> </tr> </tbody> </table> <p>* only present in the climate projection (cc) files</p> <p>2) xlsx with balancing authority data by tab</p> <p>3) csv by balancing authority:</p> <p>for historical data: year, <em>month</em>, and <em>HUC4_group</em> columns are the same as above. Data column headers are <em>class</em>_<em>forcing</em>_<em>model</em>_<em>hp</em> and with the units <em>MWh per month</em>.</p> <p>for climate projection (cc) data: year, <em>month</em>, and <em>HUC4_group</em> columns are the same as above. Data column headers are <em>class</em>_<em>forcing</em>_<em>model</em>_<em>hp_gcm_ds</em> and with the units <em>MWh per month</em>.</p>
Water risks to hydropower projects in the face of climate change
<p>This repository hosts the main outputs from an analysis using the <a href="https://waterriskfilter.org/">WWF Water Risk Filter</a> to demonstrate how one such tool can be used to screen for a variety of risks at a global scale, including risks to riverine ecosystems from both climate change and hydropower as well as risks to hydropower projects — and operators, owners, and investors — from climate change and potential regulatory or reputational risk arising from negative impacts to ecosystems. The study <a href="https://www.mdpi.com/2073-4441/14/5/721">Using the WWF Water Risk Filter to Screen Existing and Projected Hydropower Projects for Climate and Biodiversity Risks (DOI 10.3390/w14050721) </a>was published in the special issue of the MDPI journal Water: <a href="https://www.mdpi.com/journal/water/special_issues/hydrometeorological_hazards">"Hydro-Meteorological Hazards under Climate Change"</a>.</p> <p>This product incorporates data from the GRanD v1.3 database which is © Global Water System Project (2011), and from the FHReD database beta version, both datasets available at <a href="http://globaldamwatch.org/">globaldamwatch.org</a> . The source code used in this study is available at <a href="https://github.com/rafaexx/hydropowerClimateChange">https://github.com/rafaexx/hydropowerClimateChange</a></p> <p>See the interactive maps using this data at <a href="https://rcamargo.shinyapps.io/HydropowerClimateChange">https://rcamargo.shinyapps.io/HydropowerClimateChange</a></p>
CONUS-wide HUC4 Watershed Scale Hydropower Projections derived from 9505 Third Assessment
<p>This dataset provides historical and climate projection monthly hydropower generation timeseries for HUC4 watersheds within the contiguous U.S. (CONUS). These data were developed as an extension to the Department of Energy Water Power Technologies Office's SECURE Water Act Section 9505 Third Assessment (9505) and include both federal and non-federal hydropower facilities. Additional modeling detail can be found in <a href="https://iopscience.iop.org/article/10.1088/1748-9326/ad6ceb">Broman et al., 2024</a> and in the article's <a href="https://github.com/9505-PNNL/broman-etal_2024_erl">metarepository</a>. Note that in some instances multiple HUC4 watersheds have been merged together into a HUC4 group, and that HUC4 watersheds without hydropower facilities are excluded. A hydropower facility's physical location, rather than the source of water, was used in assigning facilities to HUC4 watersheds.</p> <p>The dataset is provided in three separate formats to facilitate ease of use:</p> <p>1) Machine-readable csv in 'tidy' data format:</p> <table> <tbody> <tr> <td><strong>Short Name</strong></td> <td><strong>Unit</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>class</td> <td>N/A</td> <td>simulation type; control: historical, cc: climate scenario</td> </tr> <tr> <td>forcing</td> <td>N/A</td> <td>meteorological forcing used to drive hydrology model</td> </tr> <tr> <td>model</td> <td>N/A</td> <td>hydrology model</td> </tr> <tr> <td>hp</td> <td>N/A</td> <td>hydropower model</td> </tr> <tr> <td>gcm*</td> <td>N/A</td> <td>global climate model name</td> </tr> <tr> <td>ds*</td> <td>N/A</td> <td>downscaling method; DBCCA (statistical), RegCM (dynamical)</td> </tr> <tr> <td>HUC4_group</td> <td>N/A</td> <td>HUC4 group; HUC4 numeric ID or multiple IDs</td> </tr> <tr> <td>year</td> <td>N/A</td> <td>year</td> </tr> <tr> <td>month</td> <td>N/A</td> <td>month</td> </tr> <tr> <td>modeled_generation_MWh</td> <td>MWh per month</td> <td>simulated generation</td> </tr> </tbody> </table> <p>* only present in the climate projection (cc) files</p> <p>2) xlsx with HUC4 group data by tab</p> <p>3) csv by HUC4 group:</p> <p>for historical data: year, <em>month</em>, and <em>HUC4_group</em> columns are the same as above. Data column headers are <em>class</em>_<em>forcing</em>_<em>model</em>_<em>hp</em> and with the units <em>MWh per month</em>.</p> <p>for climate projection (cc) data: year, <em>month</em>, and <em>HUC4_group</em> columns are the same as above. Data column headers are <em>class</em>_<em>forcing</em>_<em>model</em>_<em>hp_gcm_ds</em> and with the units <em>MWh per month</em>.</p>
Multi-model Hydropower Projections for the United States Federal Power Marketing Areas under CMIP5 Climate Change Conditions
<p>This dataset contains an ensemble of monthly hydropower generation projections for the United States Federal Hydropower plants for the periods of 1966-2005 (historical period) and 2011-2050 (future period). The dataset includes the monthly hydropower projections developed in (Kao et al. 2016) based on the Watershed Runoff-Energy Storage (WRES) model and is complemented with another ensemble based on the process-based Water Management Power (WMP) model.</p> <p>The hydrologic projections are estimated through a cascading modeling toolchain that include ten global climate change model projections (ACCESS1-0, BCC-CSM1-1, CCSM4, CMCC-CM, GFDL-ESM2M, MIROC5, MPI-ESM-MR, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) under RCP8.5 scenario, which are dynamically downscaled with a regional climate model (RegCM4) ( Pal et al. 2007, Giorgi et al. 2012)), which then inform the Variable Infiltration Capacity (VIC) hydrology model (Liang et al. 1994). The ensemble of hydrologic projections is then informing two processes to translate runoff into hydropower projections. First, WRES models monthly river routing and employs a non-linear statistical approach relating monthly natural flow to hydropower generation, including processes such as spilling. Second, MOSART-WM (Voisin et al. 2013), a large-scale river routing and water management model, provides daily reservoir storage and regulated release at dam locations as well as regulated flow at run-of-the-river power plants. The WMP model then translates reservoir and regulated river dynamics into hydropower projections (Zhou et al. 2018). Those projections are further calibrated to monthly generation provided by the federal utilities. The US federal hydropower plants analyzed in this study include 132 facilities that were built and/or are operated by the US Army Corps of Engineers (USACE), the Bureau of Reclamation (Reclamation), and the International Boundary and Water Commission (IBWC). The electricity generation projected for these hydropower plants were aggregated by four Power Marketing Administrations (PMAs), including Bonneville Power Administration (BPA), Southeastern Power Administration (SEPA), Southwestern Power Administration (SWPA), and Western Area Power Administration (WAPA), and their associate subregions.</p> <p>The two files, <em>SWA9505V2_Gsim_PMA_WRES.mat</em> and <em>SWA9505V2_Gsim_PMA_WMP.mat</em>, represent model outputs from the two hydropower models, WRES and WMP respectively.</p> <p>Each file contains 6 variables:</p> <p>1) “Models”: the 10 global climate models (GCMs).</p> <p>2) “PMA_areas”: the 18 subregions of PMAs as defined in (Kao et al. 2015).</p> <p>3) “PMA_G_mn_6605”: 1966-2005 projected monthly hydropower generation for each PMA sub-regions. Dimension: (12 [months], 40 [years], 18 [subregions], 10 [GCMs]). Unit: MWH.</p> <p>4) “PMA_G_mn_1150”: Same as “PMA_G_mn_6605”, but for 2011-2050 projected hydropower generation.</p> <p>5) “PMA_G_yr_6605”: 1966-2005 projected annual hydropower generation. Dimension: (40 [years], 18 [subregions], 10 [GCMs]) . Unit: MWH.</p> <p>6) “PMA_G_yr_1150”: Same as “PMA_G_yr_6605”, but for 2011-2050 projected hydropower generation.</p> <p>The following journal paper details the method in creating the dataset:</p> <p><strong>Impacts of Climate Change on Subannual Hydropower Generation: A Multi-model Assessment of the United States Federal Hydropower Plants</strong></p> <p><strong>Zhou et al. (2022) Preparing for submission to Environmental Research Letters.</strong></p>
GODEEEP-hydro - Historical and projected power system ready hydropower data for the United States
<p>This dataset contains monthly and weekly hydropower generation and generation constraints (min, max, daily range) for over 1,400 hydropower plants in the conterminous United States. The dataset includes a historical period (1982-2019) and a future period (2020-2099) with 4 future warming scenarios.</p> <p>For more information please refer to Bracken et al. 2024, godeeep_hydro: Historical and projected power system ready hydropower data for the United States, in prep, or refer to the Github repository https://github.com/GODEEEP/tgw-hydro</p> <h3>Data description</h3> <p>The dataset contains 10 data files with the naming convention <code><scenario>_<monthly/weekly>.csv</code> where scenario can be either "historical", "rcp45cooler", "rcp45hotter", "rcp85cooler", or "rcp85hotter". "monthly" or "weekly" refers to the timestep of the data.</p> <ul> <li>datetime - The datetime stamp of the current timestep</li> <li>eia_id - An integer value with the EIA plant code that represents the facility</li> <li>plant - The name of the facility according to the EIA</li> <li>power_predicted_mwh - The total energy gnerated over the period in MWh, aka the energy target</li> <li>n_hours - The number of hours in the period, useful for converting between power and energy</li> <li>p_avg - Average power generation for the period</li> <li>p_max - Maximum allowable power generation for the period</li> <li>p_min - Minimum allowable power generation for the period</li> <li>ador - Average daily operational range for any given day in the period</li> <li>scenario - The name of the scenario, either "historical", "rcp45cooler", "rcp45hotter", "rcp85cooler", or "rcp85hotter"</li> </ul> <p>Also included is the metadata file <code>godeeep_hydro_plants.csv</code> which contains metadata for each hydropower plant that is included in the dataset. Each row in this file refers to one hydropower facility. This file has the following columns:</p> <ul> <li>eia_id - An integer value with the EIA plant code that represents the facility</li> <li>plant - The name of the facility according to the EIA</li> <li>mode - Either "Storage" or "RoR" indicating if the plant is primarily operated as a storage or ron-of-river facility</li> <li>state - Two letter U.S. state name</li> <li>lat - Latitude of the facility</li> <li>lon - Longitude of the facility</li> <li>nameplate_capacity - The total nameplate capacity of the facility according to the EIA</li> <li>nerc_region - Four letter code for the NERC region of the facility</li> <li>ba - Balacing authority of the facility</li> <li>max_param - Value of the a_{max} parameter used to derive p_max</li> <li>min_param - Value of the a_{min} parameter used to derive p_min</li> <li>ador_param - Value of the a_{ador} parameter used to derive ador</li> <li>huc2 - Two digit hydrologic unit code (HUC) which contains the facility</li> </ul> <h3>Funding</h3> <p>This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).</p> <p>PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.</p> <p>Corresponding author:</p> <p>Cameron Bracken, cameron.bracken@pnnl.gov</p> <p>v1.1.0 - Update file naming convention</p>
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