This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python. This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility. Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case. New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.

This data submission includes the raw time-lapse ERT (electrical resistivity tomography) monitoring data, flow system data, operator logs, E4D (https://e4d.pnnl.gov) inversion files, and metadata necessary to reproduce the 4D ERT inversion for the Oct. 24 through Nov. 7 2018 post-stimulation flow test in test bed 1. The tests were done at the Sanford Underground Research Facility at Homestake Mine in South Dakota.

Electric Vehicle charging facilities owned by Fingal County Council.  This data set list refers only to chargers available to the public which are owned and managed by Fingal County Council. Fingal Fleet have Electrical Points and Chargers in all the Fingal County Council Buildings and Depots Further charging points are run by private companies and can see the link below. There are more an more Electric Charging points been added to the network by ESB Networks Ireland and other network providers.  E.S.B own and maintain around 1350 public points approx. See link below   www.esb.ie/ecars and follow the link to see nationwide points

The submission is the combined design report for the HydroAir Power Take Off (PTO). CAD drawings, circuit diagrams, design report, test plan, technical specifications and data sheets are included for the Main and auxiliary control cabinets and three-phase-synchronous-motor with a permanent magnet generator (PMG).

Research references to literature about the Newberry geothermal area, Oregon.

The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the datasets. This dataset contains synthetic detailed electrical distribution network models, and connected timeseries loads for the greater San Francisco (SFO), Greensboro, and Austin areas. It is intended to provide researchers with very realistic and complete models that can be used for extensive powerflow simulations under a variety of scenarios. The data is synthetic, but has been validated against thousands of utility feeders to ensure statistical and operational similarity to electrical distribution networks in the US. The OpenDSS data is partitioned into several regions (each zipped separately). After unzipping these files, each region has a folder for each substation, and subsequent folders for each feeder within the substation. This allows users to simulate smaller sections of the full dataset. Each of these folders (region, substation and feeder) has a folder titled "analysis" which contains CSV files listing voltages and overloads throughout the network for the peak loading time in the year. It also contains .png files showing the loading of residential and commercial loads on the network for every day of the year, and daily breakdowns of loads for commercial building categories. Time series data is provided in the "profiles" folder including real and reactive power at 15 minute resolution along with parquet files in the "endues" folder with breakdowns of building end-uses.

The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater, geomechanical models, gravity surveys, magnetics, resistivity, magnetotellurics (MT), rock physics, stress, the geologic setting, and supporting documentation, including several papers. Also included are 3D models (Petrel and Jewelsuite) of the proposed site. Data for wells INEL-1, WO-2, and USGS-142 have been included as links to separate data collections. These data have been assembled by the Snake River Geothermal Consortium (SRGC), a team of collaborators that includes members from national laboratories, universities, industry, and federal agencies, lead by the Idaho National Laboratory (INL). Other contributors include the National Renewable Energy Laboratory (NREL), Lawrence Livermore National Laboratory (LLNL), the Center for Advanced Energy Studies (CEAS), the University of Idaho, Idaho State University, Boise State University, University of Wyoming, University of Oklahoma, Energy and Geoscience Institute-University of Utah, US Geothermal, Baker Hughes Campbell Scientific Inc., Chena Power, US Geological Survey (USGS), Idaho Department of Water Resources, Idaho Geological Survey, and Mink GeoHydro.

MT is measured in the field by using induction coils to measure the time-varying magnetic source for frequencies between 1000-0.001~Hz, and electric dipoles to measure the Earth's electrical response. Because the magnetic source field is polarized, orthogonal directions of the fields need to be measured to get a complete description of the fields. In all measurements collected for this project, induction coils and electric dipoles were aligned with geomagnetic north and east. MT data were collected at 22 stations with a ZEN 32-bit data logger developed by Zonge International, magnetic fields were measured with ANT-4 induction coils, and electric fields where measured with Ag-AgCl reference electrodes from Borin on 50~m dipoles. The data was collected on a repeating schedule of 10~min at 4096~samples/s and 7 hours and 50 minutes at 256 samples/s over a 20-24 hour period. To convert time series data into the frequency domain and get estimations of the impedance tensor, the processing code BIRRP was used (Chave & Thompson 2004). Simultaneous measurements were used as remote references to reduce noise and bias in the data. Chave, A. D., & Thomson, D. J. 2004. Bounded inuence magnetotelluric response function estimation. Geophys. J. Int., 157, 988-1006.