Distribution System Network Resilience Enhancement Against Predicted Hurricane Events Using Statistical Probabilistic System Line Damage Prediction Model

Abstract

To enhance the resilience of the distribution power system network against hurricane events, quality proactive operational planning is required. The first action is to leverage the oncoming predicted hurricane events data for accurate proactive prediction of system line outage under hurricane events. In this article, a hybrid system line outage prediction method based on a statistical probabilistic system components fragility curve (FC), Monte-Carlo simulation (MCS), and scenario reduction algorithm (SCENRED) is proposed. The proposed hybrid model is meant to consider the system network configuration and the hurricane dynamic as the two main causes of grid topology failure during contingencies. Hurricane historical data are used to develop the system line outage prediction model. This model is investigated on a standard IEEE 15-bus test system. The system line outage prediction results validate the effectiveness of the proposed system component's FC-MCS-SCENRED model. The system line outage prediction provides further insights into the proactive system network optimal reconfiguration against hurricane events hence enhances grid resilience against hurricane event via operational planning.