Abstract:
Electrification of the transportation sector and provision of effective and well-designed charging infrastructure to vehicle owners is an important task. This thesis depicts the modeling of an 11kV Gulshan-e-Iqbal residential feeder from the data provided by Lahore Electric Supply Company (LESCO) of Pakistan. The modeled feeder provides power to Gulshan Iqbal Block of Allama Iqbal Town in Lahore. According to the map of the respective feeder, 458 houses are connected to it. If we consider the least penetration of chargers, then one charger must be connected to each load bus, which sums up to 13.1% induction according to calculations. After the addition of level 2 chargers to some random five places, the calculated percentage becomes 1%, a total of which considers 14.1% penetration on the feeder. According to the Pakistani government's Electric Vehicles Policy 2020-2025, the penetration rate of electric vehicles will reach 20% by 2025 and 30% by 2030. Probabilistic analyses are performed for 10%, 20%, and 30% penetration. Analysis of voltage profiles, line loading percentages, and secondary transformer loading has been performed after 14.1% penetration of level 1 and level 2 EV chargers. Nodes having weak hosting capacity have been highlighted. The violations of critical parameters caused by increased grid load due to installation of possible EV load have been addressed with feasible solutions. The data provided was in the format of Synergi, a licensed software, which redirected our research to the use of PandaPower, an open-source software, in Jupyter Notebook. The use of OpenDSS and PyCharm was also part of our research work while extracting the exact data to perform the following studies. Our studies can help to improvise the planning in the management of anticipated EV load in the grid and highlight the problematic nodes which need reinforcement.
