Predicting Lightning-Related Outages in Power Distribution Systems: A Statistical Approach

Milad Doostan,Badrul Chowdhury

doi:10.1109/access.2020.2991923

Abstract

This paper presents a novel data-driven approach for predicting lightning-related outages that occur in power distribution systems on a daily basis. In order to develop an approach that is able to successfully fulfill this objective, there are two main challenges that ought to be addressed. The first challenge is to define the extent of the target area. An unsupervised machine learning approach is proposed to overcome this difficulty. The second challenge is to adequately identify characteristics of lightning-related outages and to explore the relationship between these outages and weather-related variables (thunderstorm events). In this paper, these outages are clustered into a few manageable groups. Then, a probabilistic model is presented to estimate the likelihood of each group of outages. Finally, a machine learning classification algorithm that can handle the imbalanced problem is developed to predict what group will the outage belong to on a specific day in a specific area of the system under study. Actual outage data, obtained from a major utility in the U.S., in addition to radar weather forecast data are utilized to build the proposed approach. Also, three case studies are provided to show several issues associated with predicting lightning-related outages, and to demonstrate how the proposed approach can address those problems adequately.

Highlights

Lightning is a major cause of outages in power distribution systems [1]
While taking such preventive actions appear to be effective for protecting the system against severe damages, momentary outages caused by the activation of these protective devices can exert
Chowdhury: Predicting Lightning-Related Outages in Power Distribution Systems: A Statistical Approach tremendous improvements in weather forecasting efforts, a massive amount of outage and weather data has become available in recent years

Summary

INTRODUCTION

Lightning is a major cause of outages in power distribution systems [1]. Transient over-voltages caused by direct or indirect lightning strikes may inflict severe damages to the susceptible equipment and can produce detrimental effects on power quality and reliability of the system. Chowdhury: Predicting Lightning-Related Outages in Power Distribution Systems: A Statistical Approach tremendous improvements in weather forecasting efforts, a massive amount of outage and weather data has become available in recent years. As a matter of fact, a majority of these approaches are developed based on the combination of weather-related outages and cannot to be used for predicting only lightning-related outages They mostly consider the entire distribution system under study for the prediction task; do not provide the ability to make the prediction for a specific area within the system.

DATA DESCRIPTION

CLUSTERING THE OUTAGES

LIKELIHOOD OF OUTAGES

PREDICTING OUTAGES

Findings

VIII. CONCLUSION