Data from: Modeling Tools for Analyzing Electrical Power Distribution Systems Impacted by Electric Vehicle Load Growth
Portland State University. Department of Electrical and Computer Engineering
Smart power grids, Electric power distribution, Electric vehicles -- Energy consumption
A suite of distribution system analysis tools has been developed using CYME 7.1 and Python 2.7 for evaluating the impacts from electric vehicle penetration, particularly overloading and under-voltage events. Two of these tools apply new loads to and create intentional spotloads on a model distribution system. Two other tools incorporate time series demands for EV loads and provide load growth within the model system. A fifth tool provides data collection for overloading and under-voltage events.
Using these EV evaluation tools, users can study how a distribution system may be impacted due to EV load growth and stochastic EV placement. These tools allow for a representation of how the system changes with increased EV penetration.
The dataset supports a Master of Science (M.S.) in Electrical and Computer Engineering thesis, Modeling Tools for Analyzing Electrical Power Distribution Systems Impacted by Electric Vehicle Load Growth. The thesis may be accessed at https://archives.pdx.edu/ds/psu/35666.
Thesis Advisor: Robert Bass, Ph.D.
This work is marked with CC0 1.0 Universal
Sheeran, Jacob, "Data from: Modeling Tools for Analyzing Electrical Power Distribution Systems Impacted by Electric Vehicle Load Growth" (2021). Electrical and Computer Engineering Datasets. 2. https://doi.org/10.15760/ece-data.02
PenetrationVsYear.csv (1 kB)
PEV-Profiles-L1.csv (44862 kB)
PEV-Profiles-L2.csv (38965 kB)
definitions.py (1 kB)
function_study_analysis.py (2 kB)
LoadFlowOverload.py (114 kB)
lookup.py (2 kB)
main.py (16 kB)
ModifySpotLoad.py (38 kB)
UserInput.py (8 kB)
The archive contains two file types.