AUTHOR=Wenskovitch John , Jefferson Brett , Anderson Alexander , Baweja Jessica , Ciesielski Danielle , Fallon Corey 

TITLE=A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

JOURNAL=Frontiers in Big Data

VOLUME=5

YEAR=2022

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2022.897295

DOI=10.3389/fdata.2022.897295

ISSN=2624-909X

ABSTRACT=<p>This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.</p>