Estimating Installed PV SSEGs on an LV Feeder using Aggregated Load Demand Data

Increasing adoption of PV SSEGs and its integration into the grid has led to increased challenge in grid management. Accurate estimation of the amount of PV SSEGs connected to the grid is key in voltage regulation, management of electricity supply for local suppliers and for the general electricity network design and security.This paper proposes a method that uses data collected during the Eskom Domestic Load Research (DLR) project as a baseline to estimate the amount of PV SSEGs that is currently installed on a low voltage network feeder in South Africa. Customer class is used to identify similar areas. The proposed approach is a non-analytical method that uses aggregated demand data from a feeder, individual customer demand data from the DLR project as well as the solar PV irradiation data. It attempts to account for stochasticity in the loads and solar irradiation and hence model an estimation tool using a probabilistic approach. Ultimately, a methodology is proposed through which an assessment of the installed PV SSEGs on a feeder can be determined using feeder aggregated demand data for a specific set of customers.March data for the year 2000 from Helderberg area in Cape Town is used in the modelling. In this study, MATLAB is used.