This dataset shows the Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) that are currently registered through Washington State Department of Licensing (DOL).

Go to https://afdc.energy.gov/stations/#/find/nearest to access the full database of alternative fuel station locations nationwide, collected and maintained by the U.S. Department of Energy National Renewable Energy Laboratory. A station appears as one point in the data and on the map, regardless of the number of fuel dispensers or charging outlets at that location. For EV charging stations for example, the data includes the number of number of charging ports available at the specific station.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

This shows the number of vehicles that were registered by Washington State Department of Licensing (DOL) each month. The data is separated by county for passenger vehicles and trucks. DOL integrates National Highway Traffic Safety Administration (NHTSA) data and the Environmental Protection Agency (EPA) fuel efficiency ratings with DOL titling and registration data to create this information.

This shows records of title activity (transactions recording changes of ownership) and registration activity (transactions authorizing vehicles to be used on Washington public roads).

This dataset contains session details from publicly available, Town-owned electric vehicle charging stations. The dataset does not include the EV charging station located at Herb Young Community Center Parking Deck (121 Wilkinson Avenue Cary, NC 27513) although it is operational. This report was pulled January 3, 2023. The dataset is updated monthly.

List of Electric Vehicle Charging Stations.

Known Electric Vehicle Charging Stations in and around the City of Houston, as maintained by the Mayor's Office of Sustainability...

This dataset has Jersey City owned public electric vehicle charging stations (Installed & proposed locations)View Map For more information, please visit - https://jcmakeitgreen.org/sustainable-mobility/

The EVSE Deployment and Grid Evaluation (EDGE) Tool is a mapping and visualization tool that provides the ability for users to assess the feasibility of deploying charging infrastructure in the context of local grid constraints.

EDGE inputs information from two sources:

• California Investor-Owned Utility (IOU) Grid Needs Assessment (GNA) datasets - The GNA data provide information regarding the amount of "headroom" that primary circuits and substations have to accommodate new load before requiring attention, such as equipment upgrades. Notably, there is no information present regarding the secondary distribution system. The GNA dataset EDGE currently uses is forecasted through 2025.
• Results from the CEC's AB 2127 Assessment Infrastructure Models, EVI-Pro and HEVI-LOAD - Hourly load profiles from both models are combined and their overall peak values are assessed.

As Electric Vehicles (EVs) become more prevalent, it's essential that EV charging infrastructure quality and accessibility evolves. Our aim is to enhance the driving experience for EV users throughout New South Wales.

To support this initiative, we have released an extensive dataset that includes destination (AC) and fast (DC) EV charging stations currently available in NSW, as well as those scheduled for future development. This dataset provides in-depth details, including the number of chargers, plug types, and power specifications. It can be used by a variety of EV stakeholders to aid planning, policy, design and customer outcomes.

Transport for NSW are committed to keeping this information current and will update the dataset every quarter to reflect the latest EV charging developments.

Note: Transport for NSW are not responsible for the collection or validation of this information. We recommend checking on the validity of this data and the operational status of the chargers with the charge point operator before relying on it. If you notice an error with this data please write to: ElectricVehicles@Transport.nsw.gov.au

Please refer to the data article where the data is described (Data-in-brief, https://doi.org/10.1016/j.dib.2024.110883).

The data article refers to the paper "A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study". The Electric Vehicle (EV) charging dataset includes detailed information on plug-in times, plug-out times, and energy charged for over 35,000 residential charging sessions, covering 267 user IDs across 12 locations within a mature EV market in Norway. Utilising methodologies outlined in the paper, realistic predictions have been integrated into the datasets, encompassing EV battery capacities, charging power, and plug-in State-of-Charge (SoC) for each EV-user and charging session. In addition, hourly data is provided, such as energy charged and connected energy capacity for each charging session.

The comprehensive dataset provides the basis for assessing current and future EV charging behaviour, analysing and modelling EV charging loads and energy flexibility, and studying the integration of EVs into power grids.

Existing public Electric Vehicle (EV) charging stations within Connecticut from US DOE map found at https://afdc.energy.gov/stations/#/find/nearest complemented with research done by DEEP as of 05/27/2020

This data was produced as part of the Energy Technologies Institute's Smart Systems and Heat Programme. It was developed to help understand the possible implications of EV charging in the context of the decarbonisation of buildings in local areas. This data is based upon real world vehicle journeys captured in the Department for Transport's National Travel Survey (NTS). Within this survey families maintain a travel diary for 7 days which contains information about all car journeys completed by the family. For families with more than one vehicle it is possible to identify which car has been used for each journey. Data collected over 8 years for a total of 67,848 vehicles was used in the analysis. This dataset contains EV charge profiles for domestic and public charge points. Domestic charge profiles are represented as both 'after diversity' demands and as 'typical' demand profiles for an individual charge point. After diversity demands represent the average charge profile across a large number of households. These will show a lower peak than the charge profile for an individual household since households will all have unique travel patterns and, therefore, will charge at different times of day. Public and Work charge profiles represent the after diversity demand, but with an assumption that these charge points are used every day.

Charging data are collected from one of three sources, each with varying levels of additional information. These sources, in approximate order from most to least additional information, are: • The electric vehicle supply equipment (charger) • Onboard the vehicle itself • From a utility submeter. Many chargers provide software that allows for the collection and reporting of charging session data. If unavailable, data may be recorded by the charging vehicle’s onboard systems. If neither of these options is available, data can be acquired from utility submeters that simply track the energy flowing to one or more chargers. Data collected directly from the electric vehicle supply equipment (EVSE) are typically the most accurate and highest frequency. However, it is not always possible to discern which exact vehicle is being charged during any one session. EVSE-side data can be identified where a single charger ID but a range of vehicle IDs are present (e.g., CH001, EV001-EV005). Data collected from the vehicle’s onboard systems usually does not provide information on which exact charger is being used. Vehicle-side data can be identified where a single Vehicle ID but a range of Charger IDs are present (e.g., EV001, CH001-CH005). Data collected from utility submeters provide no information on which specific vehicle is charging or which specific charger is in use. Submeter data can be identified where multiple Vehicle IDs and multiple Charger IDs are present, but only a single Fleet ID is present (e.g., EV001-EV005, CH001-CH005, Fleet01). The Charge Data Daily/Session Dictionaries contains definitions for each available parameter collected as part of an individual charging session, aggregated at either a daily or session level. The parameters available will vary between vehicles and chargers. The Charger Attributes table contains specific charger characteristics, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. The Charger Attributes Data Dictionary contains definitions for each available parameter collected on the physical and operational characteristics of the charging hardware itself. The Vehicle Attributes Data Dictionary contains definitions for each available parameter associated with a vehicle’s physical and functional attributes and fleet context. The Vehicle Attributes table contains specific vehicle characteristics, coded to an anonymous Vehicle ID. This Vehicle ID can be used as a key between vehicle data and vehicle attribute tables, and in cases where charging data are supplied, links a vehicle with the charger(s) that supplied it power. The Charging Data tables contain the data from each charger’s operations, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. Data is being uploaded quarterly through 2023 and subject to change until the conclusion of the project.

The Statewide Electric Vehicle (EV) Charging Report, specifically focused on Virginia and Washington D.C., offers an analysis of EV infrastructure development in these regions, particularly related to major urban areas. This report typically involves assessing the current state of electric vehicle charging stations, infrastructure readiness, and efforts to facilitate EV adoption in these areas.

Electric vehicle charging infrastructure statistics, including publicly available devices and grants provided by the Office for Zero Emission Vehicles (OZEV).

• Latest electric vehicle charging device statistics
• Latest electric vehicle charging device grant scheme statistics
• Archived data and past reports
• About electric vehicle charging infrastructure statistics