The domain of interest is Energy; however, the focus is to observe the trends between the different sources used for electricity generation among Canada and its provinces from 2005 to 2016, and to compare the trends for electricity generation to electricity consumption in Canada from 2005 to 2015. The main problem that will be investigated is how much of a particular source is used for electricity generation in Canada over these eleven years and what is the least and most used source of electricity generation over Canada. It will also be observed whether the proportion of electricity generated by each source in Canada during 2016, is consistent with the proportion of electricity generated by each source in every province. Additionally electricity consumption for the provinces will be studied to determine which province consumes the most and least amounts of electricity in Canada. The significance of this problem is to understand which sources are highly used to generate electric power in the provinces and in Canada. If a source is being used the most in Canada and in the provinces, it will lead us to find possible ways to generate electricity from the least used sources, so the country and its provinces do not depend on one source for electric power. It will also be observed if the electricity generation by each province has increased, decreased or remain constant from 2005-2016. From this data we can also infer which province generates the most and least amount of electric power and determine which abundant resources are available to each province for its electricity generation. Moreover, by comparing the trends for electricity consumption and electricity generation it will be observed if any province consumes more electricity than it generates. If so we can find ways to provide that province with more electrcity by importing it from other provinces.

The Remote Communities Energy Database is a public resource that provides pertinent factual information about the generation and use of electricity and other energy sources for all remote communities in Canada. Communities are identified as remote communities if they are not currently connected to the North-American electrical grid nor to the piped natural gas network; and is a permanent or long-term (5 years or more) settlement with at least 10 dwellings. The Remote Communities Energy Database is the only national data source on energy in remote communities that is publically available on one centralized site. The Remote Communities Energy Database allows users to search and conduct analyses of remote communities and their energy context. Users are also able download the data from the Remote Communities Energy Database dataset in CSV (i.e., excel compatible) format. This data is collected from a number of sources including the remote communities themselves, local utilities, provincial and territorial government’s, Indigenous and Northern Affairs Canada (INAC), Statistics Canada, Natural Resources Canada (NRCan) and various other stakeholders.

This dataset displays energy production estimates in trillion Btu by source and by state for the year 2005. Included in the data are figures on coal, natural gas, crude oil, nuclear, renewable, and total energy production. All of which are on a trillion Btu Scale. Data is available for all 50 US states, and the District of Columbia. This information is for the year 2005. Side Notes: Includes coal recovery, market production of natural gas, lease condensate included in the crude oil, and renewable energy consumption is used as proxy.

Border crossings of electric transmission lines. 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

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

Over the past half a century, the world's electricity consumption has continuously grown, reaching approximately 27,000 terawatt-hours by 2023. Between 1980 and 2023, electricity consumption more than tripled, while the global population reached eight billion people. Growth in industrialization and electricity access across the globe have further boosted electricity demand. China's economic rise and growth in global power use Since 2000, China's GDP has recorded an astonishing 15-fold increase, turning it into the second-largest global economy, behind only the United States. To fuel the development of its billion-strong population and various manufacturing industries, China requires more energy than any other country. As a result, it has become the largest electricity consumer in the world. Electricity consumption per capita In terms of per capita electricity consumption, China and other BRIC countries are still vastly outpaced by developed economies with smaller population sizes. Iceland, with a population of less than half a million inhabitants, consumes by far the most electricity per person in the world. Norway, Qatar, Canada, and the United States also have among the highest consumption rates. Multiple contributing factors such as the existence of power-intensive industries, household sizes, living situations, appliance and efficiency standards, and access to alternative heating fuels determine the amount of electricity the average person requires in each country.

This dataset displays figures on energy consumption by source and total consumption per Capita. This information is available by state for the year 2005. This information is provided by the Energy Information Administration. Alaska tops the list of total consumption per capita, while Texas ranks highest in consumption for all other categories. Included is figures regarding coal, natural gas, petroleum, and retail electricity sales.

The presented dataset contains the following simulation-based monthly hydropower generation data for 110 facilities in British Columbia and Alberta, to support Western-US interconnect grid system studies:
1) Monthly hydropower generation estimates
2) Monthly hydropower flexibility metrics (minimum and maximum hourly generation and daily fluctuations)

The hydropower generation estimates are provided with reference to the facility list that contains the corresponding metadata for each facility.

For more details, please refer to Son et al. (2024). Monthly hydropower generation data for Western Canada to support Western-US interconnect power system studies [Manuscript submitted for publication].

Corresponding author(s): Youngjun Son (youngjun.son@pnnl.gov) and Nathalie Voisin (nathalie.voisin@pnnl.gov)

For data reproduction, please see the GitHub repository at https://github.com/GODEEEP/tgw-hydro-canada" target="_blank" rel="noopener">https://github.com/GODEEEP/tgw-hydro-canada.

Hydropower Facility List

The file, CAN_hydropower_facilities.csv, provides essential information on 146 hydropower facilities in British Columbia and Alberta, derived from https://www.eia.gov/trilateral/#!/maps" target="_blank" rel="noopener">Renewable Energy Power Plants, 1 MW or more, by Energy Source by North American Cooperation on Energy Information (NACEI). Additionally, the facility information has been updated with corresponding https://open.canada.ca/data/en/dataset/a4b190fe-e090-4e6d-881e-b87956c07977">National Hydrographic Network (NHN) Work Units, global reservoir and lake database (https://www.globaldamwatch.org/grand" target="_blank" rel="noopener">GRanD: Global Reservoirs and Dams Database and https://www.hydrosheds.org/products/hydrolakes" target="_blank" rel="noopener">HydroLAKES), diversion intake flow rates based on water license information (hydropower), and so on. Below are the descriptions for each column in the facility metadata:

• fid: Facility id according to NACEI data. New four-digit id starting with '9' are assigned for facilities with no fid in NACEI data
• Facility: Name of the facility
• X: Longitude of the facility's powerhouse
• Y: Latitude of the facility's powerhouse
• Province: Province where the facility is located
• Hydro_MW: Nameplate capacity of the facility
• NHN_Work_U: Associated NHN Work Units
• GRanD_ID: Associated reservoir id from the GRanD dataset
• HydroLAKES_ID: Associated lake id from the HydroLAKES dataset
• GINDEX: Grid id from the mosartwmpy Canada model
• GINDEX_CONUS: Grid id from the mosartwmpy CONUS model, used for facilities in the Columbia River Basin
• Basin_Note: Indicator for facilities located in the Columbia River Basin or outside of the TGW meteorological forcing domain
• WECC_ADS_2032: Indicator for facilities without the WECC ADS 2032 reference hydropower generation data
• Intake_Flow_Rate: Diversion intake flow rates based on hydropower water license information
• Type: Type of facility
• Water_License: Link to the source of water license information

Among the 146 hydropower facilities listed, only 110 facilities, which are within the TGW meteorological forcings domain and have reference hydropower generation data, are considered for monthly hydropower generation estimates.

Monthly Hydropower Generation Estimates and Flexibility Metrics

Each file contains a monthly timeseries dataset (rows: monthly timestamps) from 1981 to 2019 for 110 facilities (columns: Facility listed in CAN_hydropower_facilities.csv).

1. CAN_hydropower_monthly_generation_MWh.csv: monthly total hydropower generation in MWh
2. CAN_hydropower_monthly_p_min_MW.csv: monthly flexibility metric of minimum generation capacity in MW
3. CAN_hydropower_monthly_p_max_MW.csv: monthly flexibility metric of maximum generation capacity in MW
4. CAN_hydropower_monthly_p_ador_MW.csv: monthly flexibility metric of the daily operation range in MW

Funding Acknowledgements

This work was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at the Pacific Northwest National Laboratory (PNNL).

The PNNL is a multi-program national laboratory operated by Battelle Memorial Institute for the U.S. Department of Energy (DOE) under Contract No. DE-AC05-76RL01830.

Disclaimer

The presented dataset was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor the U.S. Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof, or Battelle Memorial Institute.

Data on the quantity of energy purchased and the energy expenses are presented at the national level, by energy source (electricity, heavy fuel oil, diesel, natural gas, etc.) and by North American Industry Classification System (NAICS). Not all combinations may be available.

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.

This dataset focuses on coal exports from Canada, US and Australia and their respective prices by destination. This database is presented in quarterly datapoints where the prices are expressed in USD per tonne. [Dataset edition 2012].

This dataset provides values for ELECTRICITY PRICE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Every two years the WECC (Western Electricity Coordinating Council) releases an Anchor Data Set (ADS) to be analyzed with a Production Cost Models (PCM) and which represents the expected loads, resources, and transmission topology 10 years in the future from a given reference year. For hydropower resources, the WECC relies on members to provide data to parameterize the hydropower representation in production cost models. The datasets consist of plant-level hydropower generation, flexibility, ramping, and mode of operations and are tied to the hydropower representation in those production cost models.

In 2022, PNNL supported the WECC by developing the WECC ADS 2032 hydropower dataset [1]. The WECC ADS 2032 hydropower dataset (generation and flexibility) included an update of the climate year conditions (2018 calendar year), consistency in representation across the entire US WECC footprint, updated hydropower operations over the core Columbia River, and a higher temporal resolution (weekly instead of monthly)[1] associated with a GridView software update (weekly hydro logic). Proprietary WECC utility hydropower data were used when available to develop the monthly and weekly datasets and were completed with HydroWIRES B1 methods to develop the Hydro 923 plus (now RectifHydPlus weekly hydropower dataset) [2] and the flexibility parameterization [3]. The team worked with Bonneville Power Administration to develop hydropower datasets over the core Columbia River representative of the post-2018 change in environmental regulation (flex spill). Ramping data are considered proprietary, were leveraged from WECC ADS 2030, and were not provided in the release, nor are the WECC-member hydropower data.

This release represents the WECC ADS 2034 hydropower dataset. The generator database was first updated by WECC. Based on a review of hourly generation profiles, 16 facilities were transitioned from fixed schedule to dispatchable (380.5MW). The operations of the core Columbia River were updated based on Bonneville Power Administration's long-term hydro-modeling using 2020-level of modified flows and using fiscal year 2031 expected operations. The update was necessary to reflect the new environmental regulation (EIS2023). The team also included a newly developed extension over Canada [4] that improves upon existing data and synchronizes the US and Canadian data to the same 2018 weather year. Canadian facilities over the Peace River were not updated due to a lack of available flow data. The team was able to modernize and improve the overall data processing using modern tools as well as provide thorough documentation and reproducible workflows [5,6]. The datasets have been incorporated into the 2034 ADS and are in active use by WECC and the community.

WECC ADS 2034 hydropower datasets contain generation at weekly and monthly timesteps, for US hydropower plants, monthly generation for Canadian hydropower plants, and the two merged together. Separate datasets are included for generation by hydropower plant and generation by individual generator units. Only processed data are provided. Original WECC-utility hourly data are under a non-disclosure agreement and for the sole use of developing this dataset.

[1] Voisin, N., Harris, K. M., Oikonomou, K., Turner, S., Johnson, A., Wallace, S., Racht, P., et al. (2022). WECC ADS 2032 Hydropower Dataset (PNNL-SA-172734). See presentation (Voisin N., K.M. Harris, K. Oikonomou, and S. Turner. 04/05/2022. "WECC 2032 Anchor Dataset - Hydropower." Presented by N. Voisin, K. Oikonomou at WECC Production Cost Model Dataset Subcommittee Meeting, Online, Utah. PNNL-SA-171897.).

[2] Turner, S. W. D., Voisin, N., Oikonomou, K., & Bracken, C. (2023). Hydro 923: Monthly and Weekly Hydropower Constraints Based on Disaggregated EIA-923 Data (v1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8212727

[3] Stark, G., Barrows, C., Dalvi, S., Guo, N., Michelettey, P., Trina, E., Watson, A., Voisin, N., Turner, S., Oikonomou, K. and Colotelo, A. 2023 Improving the Representation of Hydropower in Production Cost Models, NREL/TP-5700-86377, United States. https://www.osti.gov/biblio/1993943

[4] Son, Y., Bracken, C., Broman, D., & Voisin, N. (2025). Monthly Hydropower Generation Dataset for Western Canada (1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14984725

[5] https://github.com/HydroWIRES-PNNL/weccadshydro/

Dataset Files:

Data Description:

Each dataset contains the following column headers:

Data Source (Method)

The dataset contains data from four different data sources, developed using different methods:

Companies importing and exporting electricity hold regulatory authorization from the CER and are required to report their export/import activities each month. Generated electricity not consumed domestically is exported. Electricity trade with United States is affected by prices, weather, power-line infrastructure and regional supply and demand. All these cause trade to vary from year to year. Canada also imports some electricity from the United States. The integrated Canada-US power grid allows for bi-directional flows to help meet fluctuating regional supply and demand. This dataset provides historical import and export volumes, values, and prices (by year and month) broken out by source and destination.

Gate to gate life cycle inventory (LCI) data for the US national grid. Includes generation and transmission of electricity for US electricity grid. Representative of year 2008 mix of fuels used for utility electricity generation in US. Fuels include biomass, coal, petroleum, geothermal, natural gas, nuclear, solar, hydroelectric and wind energy sources.

This data was developed by:

• Alberta Carpenter, NREL
• Chris Goemans, Athena Institute

Data is derived from reports from EIA, IEA, US DOE, Statistics Canada, USEPA, and NERC. A methodology report is available online at the USLCI Database website (http://www.nrel.gov/lci/)

Data is also available with additional information and in ecospold (XLS and XML) formats at the USLCI Database website (http://www.nrel.gov/lci/).

This dataset displays the amounts renewable energy that was consumed on a national basis for over 220 countries. This data covers the years from 1980 to 2005. This data includes statistics on renewable energy other than hydroelectric consumption, which will be shown in a separate dataset. This data was collected from the Energy Information Administration. It was taken from their: International Energy Annual 2005. Table Posted: September 13, 2007. Next Update: June 2008. This data is directly available at: http://www.eia.doe.gov/fuelrenewable.html Access Date: November 8, 2007

Total-Assets Time Series for Ameresco Inc. Ameresco, Inc. provides energy solutions in the United States, Canada, and Europe. It operates through North America Regions, U.S. Federal, Renewable Fuels, Europe, and All Other segments. The company offers energy efficiency, infrastructure upgrades, energy security and resilience, asset sustainability, and renewable energy solutions for businesses and organizations. It also designs, develops, engineers, and installs projects that reduce the energy, as well as operations and maintenance (O&M) costs of its customers' facilities; and projects primarily include various measures customized for the facility and designed to enhance the efficiency of building systems, such as heating, ventilation, cooling, and lighting systems. In addition, the company offers renewable energy solutions and services, such as the development and construction of small-scale plants that the company owns or develops for customers that produce electricity, gas, heat, or cooling from renewable sources of energy and O&M services; and sells electricity, processed renewable gas fuel, and heat or cooling produced from renewable sources of energy. Further, the company provides photovoltaic (PV) solar energy products and systems, as well as provides consulting, and enterprise energy management services; and operates wind farms. It serves the federal, state, local governments, utilities, healthcare and educational institutions, public housing authorities, public universities, municipal utilities, and commercial and industrial customers. Ameresco, Inc. was incorporated in 2000 and is headquartered in Framingham, Massachusetts.

Net-Income Time Series for Ameresco Inc. Ameresco, Inc. provides energy solutions in the United States, Canada, and Europe. It operates through North America Regions, U.S. Federal, Renewable Fuels, Europe, and All Other segments. The company offers energy efficiency, infrastructure upgrades, energy security and resilience, asset sustainability, and renewable energy solutions for businesses and organizations. It also designs, develops, engineers, and installs projects that reduce the energy, as well as operations and maintenance (O&M) costs of its customers' facilities; and projects primarily include various measures customized for the facility and designed to enhance the efficiency of building systems, such as heating, ventilation, cooling, and lighting systems. In addition, the company offers renewable energy solutions and services, such as the development and construction of small-scale plants that the company owns or develops for customers that produce electricity, gas, heat, or cooling from renewable sources of energy and O&M services; and sells electricity, processed renewable gas fuel, and heat or cooling produced from renewable sources of energy. Further, the company provides photovoltaic (PV) solar energy products and systems, as well as provides consulting, and enterprise energy management services; and operates wind farms. It serves the federal, state, local governments, utilities, healthcare and educational institutions, public housing authorities, public universities, municipal utilities, and commercial and industrial customers. Ameresco, Inc. was incorporated in 2000 and is headquartered in Framingham, Massachusetts.

Companies importing and exporting electricity hold regulatory authorization from the CER and are required to report their export/import activities each month. Generated electricity not consumed domestically is exported. Electricity trade with United States is affected by prices, weather, power-line infrastructure and regional supply and demand. All these cause trade to vary from year to year. Canada also imports some electricity from the United States. The integrated Canada-US power grid allows for bi-directional flows to help meet fluctuating regional supply and demand. This dataset provides historical import and export volumes, values, and prices (by year and month) broken out by source and destination.

The Climate Resilience Information System (CRIS) provides data and tools for developers of climate services. This layer has historical variables in decadal increments from 1950 to 2020 derived from historical observations of air temperature and precipitation. The variables included are:Cooling degree (F) days Heating degree (F) days This layer uses data from the Livneh gridded precipitation and other meteorological variables for continental US, Mexico and southern Canada. Further processing by Esri is explained below.For each variable, there are mean values for the defined respective geography: counties, tribal areas, HUC-8 watersheds. The process for deriving these summaries is available from the CRIS Website’s About the Data. Other climate variables are available from the CRIS Data page. Additional geographies, including Alaska, Hawai’i and Puerto Rico will be made available in the future.GeographiesThis layer provides historic values for three geographies: county, tribal area, and HUC-8 watersheds.County: based on the U.S. Census TIGER/Line 2022 distribution. Tribal areas: based on the U.S. Census American Indian/Alaska Native/Native Hawaiian Area dataset 2022 distribution. This dataset includes federal- and state-recognized statistical areas.HUC-8 watershed: based on the USGS Washed Boundary Dataset, part of the National Hydrography Database Plus High Resolution. Time RangesHistoric climate threshold values (e.g. Days Over 90°F) were calculated for each year from 1950 to 2020. To ensure the layer displays time correctly, under 'Map properties' set Time zone to 'Universal Coordinated Time (UTC)' and under 'Time slider options' set Time intervals to '1 Decade'.Data CitationLivneh, B., T. J. Bohn, D. W. Pierce, F. Munoz-Arriola, B. Nijssen, R. Vose, D. R. Cayan, and L. Brekke, 2015: A spatially comprehensive, hydrometeorological data set for Mexico, the U.S., and Southern Canada 1950 - 2013. Scientific Data, 2, https://doi.org/10.1038/sdata.2015.42.Data ExportExporting this data into shapefiles, geodatabases, GeoJSON, etc is enabled.