Hind Khalifa << from SACM <<SHAHAD ABDULMOHSEN MOHAMED ALOMANI2022-06-012022-06-01https://drepo.sdl.edu.sa/handle/20.500.14154/56628The increased penetration of EV will provide substantial benefits to the environment. However, each EV will present a significant additional load to electric power distribution infrastructure, especially to radial distribution feeders. The additional load may cause transformers to operate beyond their thermal limits, unacceptable voltage drops along distribution lines, and primary conductor overloads. It is now, more than ever, vital to understand the limitations of existing infrastructure in light of an accelerating push for greener alternatives with insight that stems from modeling, simulation, and proper analysis as the backbone to a well-informed response. The objective of this work is to develop EV load growth modeling and analysis tools for distribution systems. These tools will help researchers and distribution engineers better understand the impacts EV growth will have on distribution systems. Such studies can help a utility company take appropriate action to enhance grid stability and reliability. In the following pages, three analysis tools for evaluating impacts of EV on grid infrastructure assets are presented. These tools are developed for use in the GridLAB-D modeling environment and written using Python 3.8. The analysis tools were developed to serve unique purposes. The first tool notifies a user of voltage violations. The second tool identifies conductor overloads. The third tool alerts the user of transformer overloads. These tools have been evaluated using the IEEE 13 node test feeder coupled with typical household load profiles within GridLAB-D. Using these tools, users evaluate the impacts EV loads have on distribution systems, specifically transformer overloading, voltage violations, and the overload of conductors. These tools can help utility distribution planners prepare appropriate response for anticipated EV load growth.enPower Distribution System Tools for Analyzing Impacts of Projected Electric Vehicle Load Growth Using GridLab-D