SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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Results for “Charging Profiles”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
SWS Building Electric Demand Profile
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Commercial and Residential Hourly Load Profiles for All Typical Meteorological Year 3 (TMY3) Locations in the United States
One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High-quality end-use load profiles (EULPs) provide this information and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation. To help fill this gap, the U.S. Department of Energy funded a 3-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute-resolution load profiles for all major residential and commercial building types and end uses across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described in the "Technical Report Documenting Methodology" linked in the submission.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Relationship between Sodium Content and Copper Activity for High Voltage Stability in O3-Type Layered Oxide Cathodes
Layered oxides with an O3 framework have attracted attention as cathode materials for sodium-ion batteries due to their high discharge capacity. Yet they are hampered for commercialization by poor cyclability due to structural instability during the sodium (de)intercalation process. The introduction of Cu in small fractions to the transition metal layers has been empirically observed to improve reversible specific capacity and cycling stability. Understanding the redox activity of Cu in O3-type Na x TMO 2 materials is crucial, as it could directly influence the charge compensation mechanism, voltage profile, and structural stability. However, the precise role of Cu in O3-type sodium cathodes under high-voltage cycling conditions (>4.1 V) remains insufficiently understood. To close this gap of knowledge, we studied the effect of Cu in two representative layered oxides with the same O3 stacking but different sodium stoichiometry, Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 and NaMn 1/2 Fe 1/3 Cu 1/6 O 2 . X-ray spectroscopy reveals that in Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 , Cu exhibits dual redox activity, Cu + /Cu 2+ in the pristine state and Cu 2+ /Cu 3+ upon charging in the sodium-deficient material, whereas only the Cu + /Cu 2+ redox couple is observed in the fully stoichiometric layered oxide. Furthermore, the results indicate that even a slight deficiency in sodium can significantly impact the electrochemical performance and material stability and alter the elemental redox activity of Cu.
Batteries↗
Flight Arrival Data for Each Airport
This dataset contains flight arrival data for each airport, which serves as the input for generating load profiles and estimating energy needs and fleet and charger requirements.  Distribution of annual flight arrivals across different airport categories.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Underlying Data for the EVI-RoadTrip Web Tool
The dataset contains simulation-based charging infrastructure outputs that are visualized on the EVI-RoadTrip webtool. The outputs are aggregated to lower spatial resolution (e.g., state-level, corridor-level).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
National Dataset of EV Charging Stations With Estimates of Load and Vehicle Throughput
Current data from the AFDC provide locations and many details about EV charging stations, but not estimates of their peak loads or the number of vehicles they can accommodate. This dataset will augment the AFDC charging station locations with estimates of transmission load and vehicle throughput based on engineering specifications of the chargers, charging patterns based on vehicle types, battery capacities, and user behavior.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
GSE Daily Energy Consumption for Each Airport
This dataset contains GSE daily energy consumption for each airport.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗