In the energy industry, as in many other industries, data is growing faster than the tools needed to transform it into meaningful insights, decisions, and action. In the North American electric grid, many new sensors, called phasor measurement units, have been installed to better measure, assess, and provide situational awareness to operators of the electric grid. These devices can record measurements over 60 times more frequently than currents systems, meaning more data is available.
With the growth of electric grid data, much more work in the industry has focused on creating tools that can translate the wealth of phasor measurement unit data into improved operator system awareness and which can expedite and improve operator decision making. As such, this thesis documents the efforts of the University of Illinois to create visualizations of phasor measurement unit data for the purpose of improving operator situational awareness in electric grids. Specifically, the University of Illinois team created a large-scale electric grid model; created simulations, like earthquakes and ice storms, to strain the grid model; created a software tool that automates the process of going from simulation data to its analysis; and then created several data visualizations aimed at improving real time operation of the electric grid. Though the work was done for a specific region of the U.S. electric grid, the processes that were followed, the software that was built, and the visualizations that were made can be easily extended to any electric system, and, in fact, making sure they could be generalized was a key guiding principle of our work
