scholarly journals Electric vehicle charging stations in the workplace with high-resolution data from casual and habitual users

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Omar Isaac Asensio ◽  
M. Cade Lawson ◽  
Camila Z. Apablaza
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Electric Vehicle ◽  
Optimal Power Flow ◽  
Service Providers ◽  
High Temporal Resolution ◽  
High Resolution Data ◽  
Demand Models ◽  
Charging Stations ◽  
Resolution Data

AbstractProblems of poor network interoperability in electric vehicle (EV) infrastructure, where data about real-time usage or consumption is not easily shared across service providers, has plagued the widespread analysis of energy used for transportation. In this article, we present a high-resolution dataset of real-time EV charging transactions resolved to the nearest second over a one-year period at a multi-site corporate campus. This includes 105 charging stations across 25 different facilities operated by a single firm in the U.S. Department of Energy Workplace Charging Challenge. The high-resolution data has 3,395 real-time transactions and 85 users with both paid and free sessions. The data has been expanded for re-use such as identifying charging behaviour and segmenting user groups by frequency of usage, stage of adoption, and employee type. Potential applications include but are not limited to simulating and parameterizing energy demand models; investigating flexible charge scheduling and optimal power flow problems; characterizing transportation emissions and electric mobility patterns at high temporal resolution; and evaluating characteristics of early adopters and lead user innovation.

scholarly journals New Data Buoys Watch Typhoons from Within the Storm

Eos ◽  
2017 ◽  
Author(s):  
Sen Jan ◽  
Yiing Yang ◽  
Hung-I Chang ◽  
Ming-Huei Chang ◽  
Ching-Ling Wei
Keyword(s):  
High Resolution ◽  
Numerical Model ◽  
Pacific Ocean ◽  
Real Time ◽  
Northwestern Pacific ◽  
Northwestern Pacific Ocean ◽  
Time Data ◽  
High Resolution Data ◽  
Real Time Data ◽  
Resolution Data

Advanced real-time data buoys have observed nine strong typhoons in the northwestern Pacific Ocean since 2015, providing high-resolution data and reducing the uncertainty of numerical model forecasts.

scholarly journals The NOAA FM-CW Snow-Level Radar

2017 ◽  
Vol 34 (2) ◽  
pp. 249-267 ◽  
Author(s):  
Paul E. Johnston ◽  
James R. Jordan ◽  
Allen B. White ◽  
David A. Carter ◽  
David M. Costa ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Vertical Structure ◽  
Continuous Wave ◽  
High Resolution Data ◽  
The Cost ◽  
Precipitating Clouds ◽  
Resolution Data

AbstractA vertically pointing radar for monitoring radar brightband height (BBH) has been developed. This new radar utilizes frequency-modulated continuous wave (FM-CW) techniques to provide high-resolution data at a fraction of the cost of comparable pulsed radars. This S-band radar provides details of the vertical structure of precipitating clouds, with full Doppler information. Details of the radar design are presented along with observations from one storm. Results from a calibration using these storm data show the radar meets the design goals. Eleven of these radars have been deployed and provide BBH data in near–real time.

scholarly journals Capturing high-resolution water demand data in commercial buildings

2021 ◽  
Author(s):  
Peter Melville-Shreeve ◽  
Sarah Cotterill ◽  
David Butler
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Water Demand ◽  
Rainwater Harvesting ◽  
Service Providers ◽  
Low Cost ◽  
Time Data ◽  
Smart Meters ◽  
High Resolution Data ◽  
Site Water

Abstract Water demand measurements have historically been conducted manually, from meter readings less than once per month. Leading water service providers have begun to deploy smart meters to collect high-resolution data. A low-cost flush counter was developed and connected to a real-time monitoring platform for 119 ultra-low flush toilets in 7 buildings on a university campus to explore how building users influence water demand. Toilet use followed a typical weekly pattern in which weekday use was 92% ± 4 higher than weekend use. Toilet demand was higher during term time and showed a strong, positive relationship with the number of building occupants. Mixed-use buildings tended to have greater variation in toilet use between term time and holidays than office-use buildings. The findings suggest that the flush sensor methodology is a reliable method for further consideration. Supplementary data from the study's datasets will enable practitioners to use captured data for (i) forecast models to inform water resource plans; (ii) alarm systems to automate maintenance scheduling; (iii) dynamic cleaning schedules; (iv) monitoring of building usage rates; (v) design of smart rainwater harvesting to meet demand from real-time data; and (vi) exploring dynamic water pricing models, to incentivise optimal on-site water storage strategies.

scholarly journals EMO-5: A high-resolution multi-variable gridded meteorological data set for Europe

2021 ◽  
Author(s):  
Vera Thiemig ◽  
Goncalo N. Gomes ◽  
Jon O. Skøien ◽  
Markus Ziese ◽  
Armin Rauthe-Schöch ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Meteorological Data ◽  
Heavy Precipitation ◽  
Water Vapour Pressure ◽  
Data Set ◽  
High Resolution Data ◽  
Weather Stations ◽  
Resolution Data ◽  
Precipitation Events

Abstract. In this paper we present EMO-51, a European high-resolution, (sub-)daily, multi-variable meteorological data set built on historical and real-time observations obtained by integrating data from 18,964 ground weather stations, four high-resolution regional observational grids (i.e. CombiPrecip, ZAMG - INCA, EURO4M-APGD and CarpatClim) as well as one global reanalysis (ERA-Interim/Land). EMO-5 includes at daily resolution: total precipitation, temperatures (mean, minimum and maximum), wind speed, solar radiation and water vapour pressure. In addition, EMO-5 also makes available 6-hourly precipitation and mean temperature. The raw observations from the ground weather stations underwent a set of quality controls, before SPHEREMAP and Yamamoto interpolation methods were applied in order to estimate for each 5 x 5 km grid cell the variable value and its affiliated uncertainty, respectively. The quality of the EMO-5 precipitation data was evaluated through (1) comparison with two regional high resolution data sets (i.e. seNorge2 and seNorge2018), (2) analysis of 15 heavy precipitation events, and (3) examination of the interpolation uncertainty. Results show that EMO-5 successfully captured 80 % of the heavy precipitation events, and that it is of comparable quality to a regional high resolution data set. The availability of the uncertainty fields increases the transparency of the data set and hence the possible usage. EMO-5 (release 1) covers the time period from 1990 to 2019, with a near real-time release of the latest gridded observations foreseen soon. As a product of Copernicus, the EU's Earth observation programme, EMO-5 dataset is free and open, and can be accessed at https://doi.org/10.2905/0BD84BE4-CEC8-4180-97A6-8B3ADAAC4D26 (Thiemig et al., 2021).1 EMO stands for “European Meteorological Observations”, whereas the 5 denotes the spatial resolution of 5 km.

Using high resolution data to reveal depth-dependent mechanisms that drive land subsidence: The Venice coast, Italy

2009 ◽  
Vol 474 (1-2) ◽  
pp. 271-284 ◽  
Author(s):  
L. Tosi ◽  
P. Teatini ◽  
L. Carbognin ◽  
G. Brancolini
Keyword(s):  
High Resolution ◽  
Land Subsidence ◽  
High Resolution Data ◽  
Resolution Data
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