Exploring cascading outages and weather via processing historic data

TL;DR

This paper analyzes historical power outage data to understand how weather influences cascading failures, proposing methods to incorporate weather effects into models for better prediction and simulation of outages.

Contribution

It introduces a data-driven approach to quantify weather impacts on cascading outages and suggests ways to integrate these effects into existing simulation models.

Findings

Weather significantly increases outage rates.

Weather interacts with cascading effects.

Incorporating weather improves outage modeling.

Abstract

We describe some bulk statistics of historical initial line outages and the implications for forming contingency lists and understanding which initial outages are likely to lead to further cascading. We use historical outage data to estimate the effect of weather on cascading via cause codes and via NOAA storm data. Bad weather significantly increases outage rates and interacts with cascading effects, and should be accounted for in cascading models and simulations. We suggest how weather effects can be incorporated into the OPA cascading simulation and validated. There are very good prospects for improving data processing and models for the bulk statistics of historical outage data so that cascading can be better understood and quantified.