Dr. Mike Legatt

Michael is originally from Bronx, NY. He received a masters and Ph.D. in clinical health psychology/neuropsychology from the Ferkauf Graduate School of Psychology / Albert Einstein College of Medicine, and has an MSE and is a Ph.D. candidate in energy systems engineering at UT Austin, and has been a programmer for over 20 years. As an amateur (ham) radio operator, Michael received a commendation for helping to provide emergency communications during the 2003 blackout in the northeastern United States, which sparked his interest in the psychology of energy management. He works at ERCOT to support the growth of the industry’s high-reliability organizational culture, and to reduce human error by helping to optimize human-computer interactions, supporting improved situation awareness, decision support, processing speed, and stress management. He developed the Macomber Map®, which has been credited as being instrumental in helping ERCOT operators maintain grid reliability during several record-setting wind generation levels since 2010, and through several severe weather events since 2009.

Michael researches the behavioral aspects of consumer electric use, electric vehicle to grid integration, behavioral aspects of conservation and consumer awareness in grid management, and the cybersecurity, behavioral, and reliability issues that arise with integration of new technologies across layers of the grid. He is ERCOT’s lead on a collaborative research project, studying the integration of electric vehicle charging and driver behavioral patterns with the bulk electric system. This research project looks at the viability of EVs to intelligently charge in a distributed fashion and provide ancillary services, and the financial and nonfinancial signals that support driver participation.

Research Topics

Situation awareness, behavioral energy management, human factors, cybersecurity, energy usage in poverty, high reliability organizational culture, just culture, electric vehicles, synchrophasors, network modeling (CIM), visualization, human performance on the grid, grid resilience, big data visualization and decision support

to come
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