Applying artificial intelligent code to detect disturbances within power grid systems

Chase Holley*, Morgan Holzman*, Vishal Verma, and Jignesh Solanki
Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26505

Presentation No.: 56

Assigned Category (Presentation Format): Engineering (Poster Presentations)

Student’s Major: Mechanical and Aerospace Engineering

Artificial Intelligence (AI) helps to automate tasks that have previously required human interaction and intelligence. Our aim for this research is to develop software that can be integrated in power system operations for detecting external disturbance events in power delivery to consumers. Artificial Intelligence enables the analysis of large datasets by finding patterns which can help aid in answering some of the most complex problems. Power grid systems are complex with varying sizes and connection configurations which makes it hard to detect disturbances within the systems normal operating conditions. As a first step towards developing such software, we have developed the Artificial Intelligence software framework and are in the process to test this framework on 9 bus power grid systems. The objective is to increase the resiliency of power grid systems identifying disturbances so they can be mitigated before it creates the large-scale blackout such as the recent Texas blackout.

Funding:

Program/mechanism supporting research/creative efforts: WVU's SURE program (Rita Rio & Michelle Richards-Babb)