Grid and User-optimized Planning of Charging Processes of an Electric Vehicle Fleet Using a Quantitative Optimization Model: Datasets
Description
Title: Grid and User-optimized Planning of Charging Processes of an Electric Vehicle Fleet Using a Quantitative Optimization Model: Datasets Version: 1.0 Date of Release: 05.03.2021 Identifier: doi:10.17632/36n82m2w3w.1 Permalink: http://dx.doi.org/10.17632/36n82m2w3w.1 Associated publication: [In progress] Grid and User-optimized Planning of Charging Processes of an Electric Vehicle Fleet Using a Quantitative Optimization Model Suggested citation: Please reference the associated publication above when using any datasets or materials described in Mendeley Data. Contact information: Fynn Welzel, Institute for Operations Research and Information Systems, Hamburg University of Technology, Hamburg, Germany, fynn.welzel@tuhh.de Dates of data collection: 2017/01 - 2019/12 Geographic location: Berlin and Bremen, Germany. This directory contains the following datasets: - Solar radiation profiles from HTW Berlin, Germany (see reference below) - Building load profiles from Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM, Bremen, Germany Detailed description of the data: # Solar radiation profiles in file "radiationData_htw_Berlin_0-0_35-0_0-2.txt": Radiation data in custom format (described in the file itself) to model the generated photovoltaic power. The radiation data on the horizontal plane was obtained from HTW Berlin (reference below) and converted to a south orientation and with a module inclination of 35° with the help of an algorithm from Volker Quaschning (see reference below). We refer to the publication for detailed information on how this data is used to model the photovoltaic plant. The obtained and converted data is stored in this dataset to ensure long-term access. From this dataset, the following days were selected for the cases defined in the publication: ## Clear summer day: 2017-06-02 ## Cloudy summer day: 2017-08-12 ## Clear winter day: 2017-01-17 ## Cloudy winter day: 2017-02-01 # Building load profiles in the following files: ## 2019-01-21_for_winter_days.csv: Contains the scaled building load profile on 2019-01-21, used for both winter days. ## 2019-06-12_for_summer_days.csv: Contains the scaled building load profile on 2019-06-12, used for both summer days. This data is measured, formatted and provided by Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM. The power column represents the scaled power in [kW] the building draws from the node in each of the used time intervals. This power is scaled according to the assumed number of employees working in the building as described in the publication. As one day is divided into 96 time intervals with a length of 15 minutes each, these files contain 96 lines of data with the first interval (t=0) beginning in the first line.