CDFW BIOS GIS Dataset, Contact: USWTDB United States Wind Turbine Database, Description: This data set provides industrial-scale onshore wind turbine locations in the United States through July 22, 2013, corresponding facility information, and turbine technical specifications.

The Canadian Wind Turbine Database contains the geographic location and key technology details for wind turbines installed in Canada. This dataset was jointly compiled by researchers at CanmetENERGY-Ottawa and by the Centre for Applied Business Research in Energy and the Environment at the University of Alberta, under contract from Natural Resources Canada. Additional contributions were made by the Department of Civil & Mineral Engineering at the University of Toronto. Note that total project capacity was sourced from publicly available information, and may not match the sum of individual turbine rated capacity due to de-rating and other factors. The turbine numbering scheme adopted for this database is not intended to match the developer’s asset numbering. This database will be updated in the future. If you are aware of any errors, and would like to provide additional information, or for general inquiries, please use the contact email address listed on this page.

The method to create the Wind Resource Area datasets is to:Query Power Plant point locations from the California Energy Commission, California Power Plants data set by operational status and capacity greater than or equal to 2 MW at each facility from the Quarterly Fuel and Energy Report, CEC-1304A. Plants tracked include those of at least 1 MW, which are considered of commercial size. A polygon was generated around the resulting operational, commercial wind facilities using the Aggregate Points geoprocessing tool with an aggregation distance of 15 survey miles. A 5 mile spatial buffer was added to the resulting polygons. The buffer does not represent information regarding environmental analysis. It is used only to depict plant concentration regions.

A shapefile of annual average wind resource potential for California, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 11, datum WGS 84 projection system. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

Abstract: Annual average wind resource potential of California at a 50 meter height.

Purpose: Provide information on the wind resource development potential within California.

Supplemental_Information: This data set was produced by TrueWind Solutions using their Mesomap system and historical weather data, under funding from the California Energy Commission. It has been validated by NREL and wind energy meteorological consultants. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 11, datum WGS 84 projection system. On-site measurement is strongly recommended before siting potential wind farm developments.

Other_Citation_Details: The wind power resource estimates were produced by TrueWind Solutions using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

This map illustrates the variety of median project capacity sizes across the United States and California counties for wind projects whose total nameplate capacity is greater than or equal to 1 MW. The absence of projects in the southeastern United States is attributable to low average wind speeds (United States - Annual Average Wind Speed, AWS Truepower and National Renewable Energy Lab). Hurricane strength winds are not usable with current technology. Median project capacity is a function of the statewide capacity and the number of projects within the defined area. October 1, 2021; Produced by the California Energy Commission; Projection: NAD 1983 (2011) Contiguous USA Albers; Data: Energy Information Administration (EIA-860) and the Wind Performance Reporting System (WPRS). For more information, please contact Rebecca Vail (916)477-0738, or John Hingtgen (916)510-9747.

This map illustrates the variety of median plant capacity sizes across the United States and California counties for wind plants whose total nameplate capacity is greater than or equal to 1 MW. The absence of plants in the southeastern United States and California is attributable to low average wind speeds (United States - Annual Average Wind Speed, AWS Truepower and National Renewable Energy Lab). Hurricane strength winds are not usable with current technology. Median plant capacity is a function of the statewide capacity and the number of plants within the defined area.

This is the data set behind the Wind Generation Interactive Query Tool created by the CEC. The visualization tool interactively displays wind generation over different time intervals in three-dimensional space. The viewer can look across the state to understand generation patterns of regions with concentrations of wind power plants. The tool aids in understanding high and low periods of generation. Operation of the electric grid requires that generation and demand are balanced in each period. The height and color of columns at wind generation areas are scaled and shaded to represent capacity factors (CFs) of the areas in a specific time interval. Capacity factor is the ratio of the energy produced to the amount of energy that could ideally have been produced in the same period using the rated nameplate capacity. Due to natural variations in wind speeds, higher factors tend to be seen over short time periods, with lower factors over longer periods. The capacity used is the reported nameplate capacity from the Quarterly Fuel and Energy Report, CEC-1304A. CFs are based on wind plants in service in the wind generation areas.Renewable energy resources like wind facilities vary in size and geographic distribution within each state. Resource planning, land use constraints, climate zones, and weather patterns limit availability of these resources and where they can be developed. National, state, and local policies also set limits on energy generation and use. An example of resource planning in California is the Desert Renewable Energy Conservation Plan.

By exploring the visualization, a viewer can gain a three-dimensional understanding of temporal variation in generation CFs, along with how the wind generation areas compare to one another. The viewer can observe that areas peak in generation in different periods. The large range in CFs is also visible.

This map illustrates the variety of average project capacity sizes across the United States and within the state of California, for wind projects whose total nameplate capacity is greater than or equal to 1 MW (20 CCR § 1385). Average project capacity is a function of the statewide, or countywide, nameplate capacity and number of projects within the defined area. The absence of projects in the southeastern United States is arbitrable to low average wind speeds (United States - Annual Average Wind Speed, AWS True power and National Renewable Energy Lab), and insufficient hurricane-resistant technology. 1 August 2019 Produced by the California Energy Commission Projection: NAD 1983 (2011) USA Congruous Albers Equal-Area Conic Authors: Dylan Kojimoto (916) 651-0477, John Hingtgen (916) 657-4046, Brandon Davis Data: Energy Information Administrator (EIA-860) and Wind Performance Reporting System (WPRS)

This data includes the average wind speed measured at various sites throughout the Yukon over discrete time periods from as early as 1944 to as recent as 2004. The specific time periods are included in the dataset, as is a brief description of each site. Other sites will be added as the data becomes available. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

The CEC Power Plant geospatial data layer contains point features representing power generating facilities in California, and power plants with imported electricity from Nevada, Arizona, Utah and Mexico. The transmission line, substation and power plant mapping database were started in 1990 by the CEC GIS staffs. The final project was completed in October 2010. The enterprise GIS system on CECs critical infrastucture database was leaded by GIS Unit in November 2014 and was implemented in May 2016. The data was derived from CECs Quarterly Fuel and Energy Report (QFER), and Renewable Energy Action Team (REAT). The sources for the power plant point digitizing are including sub-meter resolution of Digital Globe, Bing, Google, ESRI, and NAIP aerial imageries, with scale at least 1:10,000. Occasionally, USGS Topgraphic map, Google Street View and Bing Birds Eye are used to verify the precise location of a facility. Although a power plant may have multiple generators, or units, the power plant layer represents all units at a plant as one feature. Detailed attribute information associated with the power plant layer includes CEC Plant ID, Plant Label, Plant Capacity (MW), General Fuel, Plant Status, CEC Project Status, CEC Docket ID, REAT ID, Plant County, Plant State, Renewable Energy, Wind Resource Area, Local Reliability Area, Sub Area, Electic Service Area, Service Area Category, Califormia Balancing Authorities, Califormia Air District, California Air Basin, Quad Name, Senate District, Assembly District, Congressional District, Power Porject Web Link, CEC Link, Aerial, QRERGEN Comment, WPRS Comment, Geoscience Comment, Carto Comment, QFERGEN Excel Link, WPRS Excel Link, Schedule 3 Excel Link, and CEC Data Source. For power plant layer which is joined with QFer database, additional fields are displayed: CEC Plant Name (full name), Plant Alias, EIA Plant ID, Plant City, Initial Start Date, Online Year, Retire Date, Generator or Turbine Count, RPS Eligible, RPS Number, Operator Company Name, and Prime Mover ID. In general, utility and non-utility operated power plant spatial data with at least 1 MW of demonstrated capacity and operating status are distributed. Special request is required on power plant spatial data with all capacities and all stages of status, including Cold Standby, Indefinite Shutdown, Maintenance, Non-Operational, Proposed, Retired, Standby, Terminated, and Unknown.

The purpose of this project is to determine the most suitable location for a wind farm in 50Kms radius of Calgary. Different criterion need to be considered for choosing the final site, ranging from distance from settlements, water bodies, proximity to power lines to slope and wind speed intensity of the region. Based on the literature review, the areas that did not have the potential for hosting wind turbines were excluded by using the buffer tool in ArcGIS Pro. Afterwards, the wind speed and slope of the remaining regions were analyzed to pick the location with the highest wind speed and the most suitable slope. As can be seen in the final map, the final site is located in the western side of Calgary.

This map illustrates the variety of median project capacity sizes across the United States and California counties for wind projects whose total nameplate capacity is greater than or equal to 1 MW. The absence of projects in the southeastern United States is attributable to low average wind speeds (United States - Annual Average Wind Speed, AWS Truepower and National Renewable Energy Lab). Hurricane strength winds are not usable with current technology. Median project capacity is a function of the statewide capacity and the number of projects within the defined area. August 3, 2022; Produced by the California Energy Commission; Projection: NAD 1983 (2011) Contiguous USA Albers; Data: Energy Information Administration (EIA-860) and the Wind Generation Reporting System (WPRS). For more information, please contact Rebecca Vail (916)477-0738, or John Hingtgen (916)510-9747.

The site suitability criteria included in the techno-economic land use screens are listed below. As this list is an update to previous cycles, tribal lands, prime farmland, and flood zones are not included as they are not technically infeasible for development. The techno-economic site suitability exclusion thresholds are presented in table 1. Distances indicate the minimum distance from each feature for commercial scale wind developmentAttributes: Steeply sloped areas: change in vertical elevation compared to horizontal distancePopulation density: the number of people living in a 1 km2 area Urban areas: defined by the U.S. Census. Water bodies: defined by the U.S. National Atlas Water Feature Areas, available from Argonne National Lab Energy Zone Mapping Tool Railways: a comprehensive database of North America's railway system from the Federal Railroad Administration (FRA), available from Argonne National Lab Energy Zone Mapping Tool Major highways: available from ESRI Living Atlas Airports: The Airports dataset including other aviation facilities as of July 13, 2018 is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product. Available from Argonne National Lab Energy Zone Mapping Tool Active mines: Active Mines and Mineral Processing Plants in the United States in 2003Military Lands: Land owned by the federal government that is part of a US military base, camp, post, station, yard, center, or installation. Table 1

Wind

Steeply sloped areas

10o

Population density

100/km2

Capacity factor

<20%

Urban areas

<1000 m

Water bodies

<250 m

Railways

<250 m

Major highways

<125 m

Airports

<5000 m

Active mines

<1000 m

Military Lands

<3000m

For more information about the processes and sources used to develop the screening criteria see sources 1-7 in the footnotes.

Data updates occur as needed, corresponding to typical 3-year CPUC IRP planning cyclesFootnotes:[1] Lopez, A. et. al. “U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis,” 2012. https://www.nrel.gov/docs/fy12osti/51946.pdf[2] https://greeningthegrid.org/Renewable-Energy-Zones-Toolkit/topics/social-environmental-and-other-impacts#ReadingListAndCaseStudies[3] Multi-Criteria Analysis for Renewable Energy (MapRE), University of California Santa Barbara. https://mapre.es.ucsb.edu/[4] Larson, E. et. al. “Net-Zero America: Potential Pathways, Infrastructure, and Impacts, Interim Report.” Princeton University, 2020. https://environmenthalfcentury.princeton.edu/sites/g/files/toruqf331/files/2020-12/Princeton_NZA_Interim_Report_15_Dec_2020_FINAL.pdf.[5] Wu, G. et. al. “Low-Impact Land Use Pathways to Deep Decarbonization of Electricity.” Environmental Research Letters 15, no. 7 (July 10, 2020). https://doi.org/10.1088/1748-9326/ab87d1.[6] RETI Coordinating Committee, RETI Stakeholder Steering Committee. “Renewable Energy Transmission Initiative Phase 1B Final Report.” California Energy Commission, January 2009.[7] Pletka, Ryan, and Joshua Finn. “Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report.” Black & Veatch and National Renewable Energy Laboratory, 2009. https://www.nrel.gov/docs/fy10osti/46877.pdf.[8]https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Urban+Areas[9]https://ezmt.anl.gov/[10]https://www.arcgis.com/home/item.html?id=fc870766a3994111bce4a083413988e4[11]https://mrdata.usgs.gov/mineplant/Credits

Title: Techno-economic screening criteria for utility-scale wind energy installations for Integrated Resource Planning

Purpose for creation: These site suitability criteria are for use in electric system planning, capacity expansion modeling, and integrated resource planning.

Keywords: wind energy, resource potential, techno-economic, IRP

Extent: western states of the contiguous U.S.

Use Limitations

The geospatial data created by the use of these techno-economic screens inform high-level estimates of technical renewable resource potential for electric system planning and should not be used, on their own, to guide siting of generation projects nor assess project-level impacts.Confidentiality: Public

ContactEmily Leslie Emily@MontaraMtEnergy.comSam Schreiber sam.schreiber@ethree.com Jared Ferguson Jared.Ferguson@cpuc.ca.govOluwafemi Sawyerr femi@ethree.com

Mapping Resources on energy infrastructure and potential implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States. Natural Gas Processing Plants: Facilities designed to recover natural gas liquids from a stream of natural gas. These facilities control the quality of the natural gas to be marketed. Refineries: Facilities that separate and convert crude oil or other feedstock into liquid petroleum products, including upgraders and asphalt refineries. Liquefied Natural Gas Terminals: Natural gas onshore facilities used to receive, unload, load, store, gasify, liquefy, process and transport by ship, natural gas that is imported from a foreign country, exported to a foreign country, or for interior commerce. Power Plants, 100 MW or more: Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical, and/or fission energy into electric energy with an installed capacity of 100 megawatts or more. Renewable Power Plants, 1 MW or more: Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical into electric energy with an installed capacity of 1 Megawatt or more generated from renewable energy, including biomass, hydroelectric, pumped-storage hydroelectric, geothermal, solar, and wind. Natural Gas Underground Storage: Sub-surface facilities used for storing natural gas. The facilities are usually hollowed-out salt domes, geological reservoirs (depleted oil or gas field) or water bearing sands (called aquifers) topped by an impermeable cap rock. Border Crossings: Electric transmission lines, liquids pipelines and gas pipelines. Solar Resource, NSRDB PSM Global Horizontal Irradiance (GHI): Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE"). Solar Resource, NSRDB PSM Direct Normal Irradiance (DNI): Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE"). The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.

To identify renewable energy approved and pending lease areas on BLM administered lands. To provide information about solar and wind energy applications and completed projects within the State of California for analysis and display internally and externally. This feature class denotes "verified" renewable energy projects at the California State BLM Office, displayed in GIS. The term "Verified" refers to the GIS data being constructed at the California State Office, using the actual application/maps with legal descriptions obtained from the renewable energy company.

This GIS dataset consists of polygons that represent the footprints of solar powered electric generation facilities and related infrastructure in California called Solar Footprints. The location of solar footprints was identified using other existing solar footprint datasets from various sources along with imagery interpretation. CEC staff reviewed footprints identified with imagery and digitized polygons to match the visual extent of each facility. Previous datasets of existing solar footprints used to locate solar facilities include: GIS Layers: (1) California Solar Footprints, (2) UC Berkeley Solar Points, (3) Kruitwagen et al. 2021, (4) BLM Renewable Project Facilities, (5) Quarterly Fuel and Energy Report (QFER)Imagery Datasets: Esri World Imagery, USGS National Agriculture Imagery Program (NAIP), 2020 SENTINEL 2 Satellite Imagery, 2023Solar facilities with large footprints such as parking lot solar, large rooftop solar, and ground solar were included in the solar footprint dataset. Small scale solar (approximately less than 0.5 acre) and residential footprints were not included. No other data was used in the production of these shapes. Definitions for the solar facilities identified via imagery are subjective and described as follows: Rooftop Solar: Solar arrays located on rooftops of large buildings. Parking lot Solar: Solar panels on parking lots roughly larger than 1 acre, or clusters of solar panels in adjacent parking lots. Ground Solar: Solar panels located on ground roughly larger than 1 acre, or large clusters of smaller scale footprints. Once all footprints identified by the above criteria were digitized for all California counties, the features were visually classified into ground, parking and rooftop categories. The features were also classified into rural and urban types using the 42 U.S. Code § 1490 definition for rural. In addition, the distance to the closest substation and the percentile category of this distance (e.g. 0-25th percentile, 25th-50th percentile) was also calculated. The coverage provided by this data set should not be assumed to be a complete accounting of solar footprints in California. Rather, this dataset represents an attempt to improve upon existing solar feature datasets and to update the inventory of "large" solar footprints via imagery, especially in recent years since previous datasets were published. This procedure produced a total solar project footprint of 150,250 acres. Attempts to classify these footprints and isolate the large utility-scale projects from the smaller rooftop solar projects identified in the data set is difficult. The data was gathered based on imagery, and project information that could link multiple adjacent solar footprints under one larger project is not known. However, partitioning all solar footprints that are at least partly outside of the techno-economic exclusions and greater than 7 acres yields a total footprint size of 133,493 acres. These can be approximated as utility-scale footprints. Metadata: (1) CBI Solar FootprintsAbstract: Conservation Biology Institute (CBI) created this dataset of solar footprints in California after it was found that no such dataset was publicly available at the time (Dec 2015-Jan 2016). This dataset is used to help identify where current ground based, mostly utility scale, solar facilities are being constructed and will be used in a larger landscape intactness model to help guide future development of renewable energy projects. The process of digitizing these footprints first began by utilizing an excel file from the California Energy Commission with lat/long coordinates of some of the older and bigger locations. After projecting those points and locating the facilities utilizing NAIP 2014 imagery, the developed area around each facility was digitized. While interpreting imagery, there were some instances where a fenced perimeter was clearly seen and was slightly larger than the actual footprint. For those cases the footprint followed the fenced perimeter since it limits wildlife movement through the area. In other instances, it was clear that the top soil had been scraped of any vegetation, even outside of the primary facility footprint. These footprints included the areas that were scraped within the fencing since, especially in desert systems, it has been near permanently altered. Other sources that guided the search for solar facilities included the Energy Justice Map, developed by the Energy Justice Network which can be found here:https://www.energyjustice.net/map/searchobject.php?gsMapsize=large&giCurrentpageiFacilityid;=1&gsTable;=facility&gsSearchtype;=advancedThe Solar Energy Industries Association’s “Project Location Map” which can be found here: https://www.seia.org/map/majorprojectsmap.phpalso assisted in locating newer facilities along with the "Power Plants" shapefile, updated in December 16th, 2015, downloaded from the U.S. Energy Information Administration located here:https://www.eia.gov/maps/layer_info-m.cfmThere were some facilities that were stumbled upon while searching for others, most of these are smaller scale sites located near farm infrastructure. Other sites were located by contacting counties that had solar developments within the county. Still, others were located by sleuthing around for proposals and company websites that had images of the completed facility. These helped to locate the most recently developed sites and these sites were digitized based on landmarks such as ditches, trees, roads and other permanent structures.Metadata: (2) UC Berkeley Solar PointsUC Berkeley report containing point location for energy facilities across the United States.2022_utility-scale_solar_data_update.xlsm (live.com)Metadata: (3) Kruitwagen et al. 2021Abstract: Photovoltaic (PV) solar energy generating capacity has grown by 41 per cent per year since 2009. Energy system projections that mitigate climate change and aid universal energy access show a nearly ten-fold increase in PV solar energy generating capacity by 2040. Geospatial data describing the energy system are required to manage generation intermittency, mitigate climate change risks, and identify trade-offs with biodiversity, conservation and land protection priorities caused by the land-use and land-cover change necessary for PV deployment. Currently available inventories of solar generating capacity cannot fully address these needs. Here we provide a global inventory of commercial-, industrial- and utility-scale PV installations (that is, PV generating stations in excess of 10 kilowatts nameplate capacity) by using a longitudinal corpus of remote sensing imagery, machine learning and a large cloud computation infrastructure. We locate and verify 68,661 facilities, an increase of 432 per cent (in number of facilities) on previously available asset-level data. With the help of a hand-labelled test set, we estimate global installed generating capacity to be 423 gigawatts (−75/+77 gigawatts) at the end of 2018. Enrichment of our dataset with estimates of facility installation date, historic land-cover classification and proximity to vulnerable areas allows us to show that most of the PV solar energy facilities are sited on cropland, followed by arid lands and grassland. Our inventory could aid PV delivery aligned with the Sustainable Development GoalsEnergy Resource Land Use Planning - Kruitwagen_etal_Nature.pdf - All Documents (sharepoint.com)Metadata: (4) BLM Renewable ProjectTo identify renewable energy approved and pending lease areas on BLM administered lands. To provide information about solar and wind energy applications and completed projects within the State of California for analysis and display internally and externally. This feature class denotes "verified" renewable energy projects at the California State BLM Office, displayed in GIS. The term "Verified" refers to the GIS data being constructed at the California State Office, using the actual application/maps with legal descriptions obtained from the renewable energy company. https://www.blm.gov/wo/st/en/prog/energy/renewable_energy

This data is usually updated quarterly by February 1st, May 1st, August 1st, and November 1st.The CEC Power Plant geospatial data layer contains point features representing power generating facilities in California, and power plants with imported electricity from Nevada, Arizona, Utah and Mexico.The transmission line, substation and power plant mapping database were started in 1990 by the CEC GIS staffs. The final project was completed in October 2010. The enterprise GIS system on CEC's critical infrastructure database was leaded by GIS Unit in November 2014 and was implemented in May 2016. The data was derived from CEC's Quarterly Fuel and Energy Report (QFER), Energy Facility Licensing (Siting), Wind Performance Reporting System (WPRS), and Renewable Energy Action Team (REAT). The sources for the power plant point digitizing are including sub-meter resolution of Digital Globe, Bing, Google, ESRI and NAIP aerial imageries, with scale at least 1:10,000. Occasionally, USGS Topographic map, Google Street View and Bing Bird's Eye are used to verify the precise location of a facility.Although a power plant may have multiple generators, or units, the power plant layer represents all units at a plant as one feature. Detailed attribute information associated with the power plant layer includes CEC Plant ID, Plant Label, Plant Capacity (MW), General Fuel, Plant Status, CEC Project Status, CEC Docket ID, REAT ID, Plant County, Plant State, Renewable Energy, Wind Resource Area, Local Reliability Area, Sub Area, Electric Service Area, Service Area Category, California Balancing Authorities, California Air District, California Air Basin, Quad Name, Senate District, Assembly District, Congressional District, Power Project Web Link, CEC Link, Aerial, QRERGEN Comment, WPRS Comment, Geoscience Comment, Carto Comment, QFERGEN Excel Link, WPRS Excel Link, Schedule 3 Excel Link, and CEC Data Source. For power plant layer which is joined with QFer database, additional fields are displayed: CEC Plant Name (full name), Plant Alias, EIA Plant ID, Plant City, Initial Start Date, Online Year, Retire Date, Generator or Turbine Count, RPS Eligible, RPS Number, Operator Company Name, and Prime Mover ID. In general, utility and non-utility operated power plant spatial data with at least 1 MW of demonstrated capacity and operating status are distributed. Special request is required on power plant spatial data with all capacities and all stages of status, including Cold Standby, Indefinite Shutdown, Maintenance, Non-Operational, Proposed, Retired, Standby, Terminated, and Unknown.For question on power generation or others, please contact Michael Nyberg at (916) 654-5968.California Energy Commission's Open Data Portal.

Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical, and/or fission energy into electric energy with an installed capacity of 100 megawatts or more. Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States. The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. Parent Collection: North American Cooperation on Energy Information, Mapping Data