Impact Analysis of Future Probabilistic Growth of Roof Top PV in Gulshan-e-Iqbal Feeder /

Abstract

Increased intermittent PV penetration at the low voltage level of the distribution system necessitates closer attention because it can potentially aggravate the network’s technical issues such as voltage violation, overloading of substation transformers, and line overloading. In this thesis, the placement of PV at multiple locations in the distribution system was modeled using a probabilistic technique. Rather than adopting the hit-andtrial method, this strategy has the advantage of providing a practical planning approach

for assessing the implications of stochastic PV penetration in a distribution feeder. The

research

was carried out on 301-buses 11kV/ 0.41 kV MV/LV network model representing the Gulshan-e-Iqbal feeder of the Lahore Electric Supply Company grid. The feeder’s information was mapped in SynerGEE software, and analysis of network parameters was performed by applying random number theory using Pandapower in Jupyter Notebook. The advantage of the proposed approach was observed by using various combinations of PVs that can be connected to the feeder and the amount of injected active power that every node can handle. To study the impact of probabilistic penetration scenarios on performance parameters, including voltage profile and percentage loading, four different case studies were implemented and compared to the base case. The results verified the achievement of the strategy in identifying network sites with maximum voltage deviations, line overloading, and transformer overloading. Finally, the overall hosting capacity of the feeder in all four cases was also determined.