Developing a High Performance Computing Platform to Parallelize the Dynamic Contingency Analysis Tool (DCAT) for Cascading-Outage Analysis

 

POC: Nader Samaan

Researchers discuss the power grid in an electrical control room

Andrea Starr | PNNL

Background

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations of extreme events might lead to cascading outages. Cascading is a sequential process of disconnecting power system elements such as generators, transmission lines, and loads, potentially leading to a partial or complete blackout that leaves thousands of electricity consumers without electric power. These large blackouts have a significant impact on citizens, businesses, the economy, and the government.

While such blackouts are rare, they pose a substantial risk to the security and economic health of the country. Much is known about avoiding the first few failures near the beginning of a cascade, but there is a deficit of established methods for directly analyzing the risks and consequences of the longer chains of component outages.

Analyzing the risks of cascading failures and devising ways to prevent them is an evolving field of study. This study leverages utility-grade software and industry partnership to understand grid robustness against high-order contingencies and to study grid resilience in response to and recovery from extreme events.

Additionally, developing new methodologies, algorithms, and software tools is needed to incorporate the complexity of the network and assess the impacts of cascading sequences of events. Such a process will help provide an assessment of the overall risk profile associated with extreme events.