Information on grid-connected energy storage projects and relevant state and federal policies

This project provides a national unified database of residential building retrofit measures and associated retail prices and end-user might experience. These data are accessible to software programs that evaluate most cost-effective retrofit measures to improve the energy efficiency of residential buildings and are used in the consumer-facing website https://remdb.nrel.gov/ This publicly accessible, centralized database of retrofit measures offers the following benefits: Provides information in a standardized format Improves the technical consistency and accuracy of the results of software programs Enables experts and stakeholders to view the retrofit information and provide comments to improve data quality Supports building science R&D Enhances transparency This database provides full price estimates for many different retrofit measures. For each measure, the database provides a range of prices, as the data for a measure can vary widely across regions, houses, and contractors. Climate, construction, home features, local economy, maturity of a market, and geographic location are some of the factors that may affect the actual price of these measures. This database is not intended to provide specific cost estimates for a specific project. The cost estimates do not include any rebates or tax incentives that may be available for the measures. Rather, it is meant to help determine which measures may be more cost-effective. The National Renewable Energy Laboratory (NREL) makes every effort to ensure accuracy of the data; however, NREL does not assume any legal liability or responsibility for the accuracy or completeness of the information.

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.

Users can generate reports showing the amount of energy consumed by geographical area, sector (residential, commercial, industrial) classifications. The database also provides easy downloading of energy consumption data into the comma-separated values (CSV) file format.

This database represents a list of community solar projects identified through various sources as of Spring 2018. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the souces e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to Eric O'Shaughnessy at eric.oshaughnessy@nrel.gov.

Note: Find data at source. ・ The DOE Global Energy Storage Database provides research-grade information on grid-connected energy storage projects and relevant state and federal policies. All data can be exported to Excel or JSON format. As of September 22, 2023, this page serves as the official hub for The Global Energy Storage Database.

The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-throughput experiments at the National Renewable Energy Laboratory (NREL).

Note: Find data at source. ・ The California Energy Commission has created this on-line database for informal reporting purposes using numerous electricity and natural gas consumption data sources.Users can generate reports showing the amount of energy consumed by geographical area, sector (residential, commercial, industrial) classifications. The database also provides easy downloading of energy consumption data into Microsoft Excel (XLSX) and comma-separated values (CSV) file formats.

The 2005 edition of the Energy Statistics Database contains comprehensive energy statistics on more than 215 countries or areas for production, trade, transformation and intermediate and final consumption (end-use) for primary and secondary conventional, non-conventional and new and renewable sources of energy. In addition, mid-year population estimates are included to enable the computation of per capita data. Data on heating (calorific) values are also provided to enable conversion to a common unit (terajoules) for interfuel comparison and analyses.

This Transport-Energy Database (TED) covers technology, energy demand and policies relating to the transport-energy system in Laos. This Transport-Energy Database (TED) was compiled by Latsayakone Pholsena funded by the Climate Compatible Growth (CCG) programme. Data sources are linked where possible.

This dataset was compiled as part of the CCG programme for future work in constructing transport-energy decarbonisation narratives for partner countries, including Laos.

World Input Output Database (WIOD) version 2016, energy accounts for the period 2000 to 2014.Data in .mat format for each year contains energy accounts in two forms: i) gross energy use and ii) emission relevant energy use. These accounts are further subdivided into energy use by industry and direct energy use by households. Energy use by industry can be directly linked with the WIOD 2016 input output tables.Meta data contains row and column names for the datasets described above. The same data is provided in .xlslx formatData in .xlsx format for each year contains one .xlslx file. The file contains energy accounts in two forms (provided in separate sheets): i) gross energy use for industry (GrossEnergy_Industry) and direct energy use by households (GrossEnergy_Households).ii) emission relevant energy use for industry (EmRelevantEnergy_Industry) and direct energy use by households (EmRelevantEnergy_Households). All energy data is provided in terajoules (TJ). Some visualizations made using this dataset can be found here:https://factor-flow.herokuapp.comGet in touch if you have any questions or suggestions.

This dataset is an output of the Energy work package of the Water-Energy-Food-Ecosystems (WEFE) Nexus project at the European Commission's Joint Research Centre (JRC). This dataset has been created for power system modelling purposes and it is based on publicly available sources. This dataset tries to collect some basic information on all the European hydro-power plants.

The database of costs is a list of costs related to the commercialisation of a wave energy farm. The costs are collected in an Excel sheet divided into categories. This collection of costs is intended to be used in LCoE calculations. The data has been gathered through a thorough literature review.

This dataset contains the input data for modelling Chile's energy transition from 2015 to 2050. The input data is presented as follows: 1. Chile's general data, 2. Consumption nodes and transmission lines, 3. Projected high-voltage transmission lines, 4. Historical power generation capacities, 5. Projection of the final energy demand, and 6. Renewable energy potential.

Following an Order Instituting Rulemaking initiated in October 2005, amendments adopted by the Energy Commission and approved by California's Office of Administrative Law in July 2007 created two articles: Article 1, known as Quarterly Fuel and Energy Report (QFER) directed at current California energy information, and Article 2 directed at the forecast and assessment of energy loads and resources. The regulations under QFER provide for the collection of energy data relating to electric generation, control area exchanges, and natural gas processing and deliveries. The reports are submitted on forms specified by the Energy Commission's executive director. The statistics presented here are derived from the QFER CEC-1304 Power Plant Owner Reporting Form. The CEC-1304 reporting form collects data from power plants with a total nameplate capacity of 1MW or more that are located within California or within a control area with end users inside California. The information includes gross generation, net generation, fuel use by fuel type for each generator, as well as total electricity consumed on site and electricity sales for the plant as a whole. Power plants with nameplate capacity of 20 megawatts or more also provide environmental information related to water supply and water/wastewater discharge. Database and Source Files updated: June 07, 2017

The “Sustainable Energy for all (SE4ALL)” initiative, launched in 2010 by the UN Secretary General, established three global objectives to be accomplished by 2030: to ensure universal access to modern energy services, to double the global rate of improvement in global energy efficiency, and to double the share of renewable energy in the global energy mix.

SE4ALL database supports this initiative and provides country level historical data for access to electricity and non-solid fuel; share of renewable energy in total final energy consumption by technology; and energy intensity rate of improvement

Database for scenarios of "Potentials of Renewable Energy Sources in Germany and the Influence of Land Use Datasets"

The used datasets and applied methodology can be found in the paper Potentials of Renewable Energy Sources in Germany and the Influence of Land Use Datasets
. Please cite the paper if you utilize the dataset. Applied datasets among others:

• Geobasisdaten: © GeoBasis-DE / BKG (2021), ‘Digitales Basis-Landschaftsmodell (Ebenen) (Basis-DLM)’. 2021. (Conditions of use: https://sg.geodatenzentrum.de/web_public/nutzungsbedingungen.pdf)
• Geobasisdaten: © GeoBasis-DE / BKG (2021), ‘Amtliche Hausumringe Deutschland (HU-DE)’. 2021. (Conditions of use: https://sg.geodatenzentrum.de/web_public/nutzungsbedingungen.pdf)
• Geobasisdaten: ©GeoBasis-DE / BKG (2021), 3D-Gebäudemodelle LoD2 Deutschland (LoD2-DE) (2021). (Conditions of use: https://sg.geodatenzentrum.de/web_public/nutzungsbedingungen.pdf)
• UNEP-WCMC, IUCN, ‘The world database on protected areas’. 2016. Accessed: Oct. 22, 2021. [Online]. Available: https://www.protectedplanet.net/

Please be aware of the conditions of use for parts of the applied datasets (https://sg.geodatenzentrum.de/web_public/nutzungsbedingungen.pdf) if you utilize the data.

Author:Department for Energy Security & Net Zero (DESNZ)Creation date:July 2014Date of source data harvest:April 2024 Temporal coverage of source data:up to January 2024Spatial Resolution:Project locations Geometry:PointSource data URL:Renewable Energy Planning Database: quarterly extract - GOV.UK (www.gov.uk)Data terms of use:Open Government Licence v3 - Dataset can be shared openly for re-use for commercial and non-commercial purposes, with appropriate attribution.Data attribution:Contains public sector information licensed under the Open Government Licence v3.0. Dataset processed by Buro Happold in 2024 as part of the CIEN & South London sub-regional LAEPs.Workflow Diagram:N/AComments:The data and analysis developed for the sub-regional LAEP was undertaken using data available at the time and will need to be refined for a full Phase 2 LAEP. Please check here for more detailed background on the data.Whilst every effort has been made to ensure the quality and accuracy of the data, the Greater London Authority is not responsible for any inaccuracies and/or mistakes in the information provided.

DEFRAM is a project that was funded by the Swedish Energy Agency. The project started on the 10th of December 2012 and ended on May 10, 2013. The project was run at Linköping University and involved researchers from the Department of Energy Systems at Linköping University (Patrik Thollander) and the Department of Computer and Information Science at Linköping University (Eva Blomqvist), and was implemented in close cooperation with the Swedish Energy Agency (Coordinator: Lara Kruse). Project Manager was Eva Blomqvist, Linköping University. The project started from three datasets: (1) IAC's (Industrial Assessment Center) database of around 120 000 recommendations (until late 2012), which is by the way the world's largest energy audit program with more than 10,000 energy audits performed so far, (2) results from the Swedish PFE project, from the first program period, and (3) the results of the Swedish Energy Agency's energy audit support, the so-called "energy audit checks" (EKC), during 2011-2012. To demonstrate the user benefits and usefulness in linking these data sources have first created an OWL vocabulary, i.e., a new common data model for the datasets, built as a vocabulary for representing the data elements, and most of the actual data were then transferred to the RDF format, structured according to the new vocabulary. For interlinking the different data sources a number of manual mappings have been implemented. Among other things, measures were as far as possible reclassified according to a new taxonomy of task types developed by Energy Systems researchers at Linköping University. To integrate IAC data with Swedish data, a mapping was also made both between the IAC's ARC codes (action types) and the taxonomy, as well as between the industrial classification SIC (used by IAC) and the Swedish SNI-2007. The result of this work is published through a so-called SPARQL endpoint, which provides direct access to the linked data stored in an underlying triple store. In the current release (as of 2013-09), there are about 2,200 Swedish recommended measures published, and 120,000 recommendations from IAC. Access to these data can be gained through an interface for writing your own SPARQL queries, as well as a demonstration interface for end users (in Swedish), where questions can be formulated through various menu options. The complete dataset can also be downloaded as an RDF-dump. Note that a continuous quality control going on, so data can be changed and the project or its participants cannot be held responsible for any errors in the data - the results are used at your own risk. Note also that the result is a demonstration of what is possible to implement, not a full-scale operational solution - we can not guarantee the uptime and response times for the demo service. Purpose: The long term vision of the project is to make data on energy audits more accessible, both for application developers and end users, such as auditors. The goal of this project is to make available a number of datasets containing technical energy efficiency improvement measures as Linked Data on the Web (for more information on what this means see the LOD project ). The material consists essentially of two different types of data; measurements of saved energy and action proposals (proposed workarounds for energy surveys and their estimated costs and estimated future savings). Data for direct download consists 6 data files in rdf format and associated documentation.

A database of geochemical data from potential geothermal sources aggregated from multiple sources as of March 2010. The database contains fields for the location, depth, temperature, pH, total dissolved solids concentration, chemical composition, and date of sampling. A separate tab contains data on non-condensible gas compositions. The database contains records for over 50,000 wells, although many entries are incomplete. Current versions of source documentation are listed in the dataset.