Probabilistic Risk Assessment of Power Quality Variations and Events under Temporal and Spatial Characteristic of Increased PV Integration in Low-Voltage Distribution Networks

Shivananda Pukhrem, Technological University Dublin
Malabika Basu, Technological University Dublin
Michael Conlon, Technological University Dublin

Document Type Article

Abstract

The aim of this paper is to perform a probabilistic risk assessment of power quality variations and events that may arise due to high photovoltaic distributed generation (PVDG) integration in a low-voltage distribution network (LVDN). Due to the spatial and temporal behavior of PV generation and load demand, such an assessment is vital before integrating PVDG at the existing load buses. Two power quality (PQ) variations such as voltage magnitude variation and phase unbalance together with one PQ abnormal event are considered as the PQ impact metrics. These PQ impact metrics are assessed in terms of two PQ indices, namely site and system indices. A Monte Carlo based simulation is applied for the probabilistic risk assessment. From the results, site overvoltage shows a likely impact to observe as the PVDG integration increases. The probability of 20% of customers violating 1.1 p.u. at 100% penetration level is 0.5. Integration of PVDG reduces the voltage unbalance as compared with no or low PVDG penetration. There is a higher probability of observing deep sag at the site as PVDG integration increases. This probabilistic approach can be used as a tool to assess the likely impacts due to PVDG integration against the worst-case scenarios.