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Electric Grid

Advancing Cognitive Performance for Power Grid Resiliency

The increasing complexity of energy generation and use combined with natural and man made disruptions are threatening the reliability of the nation’s most vital infrastructure: the electric grid. Severe weather events, deliberate physical attacks, and cyber-attacks on grid systems are of growing concern to grid operators. To make effective decisions under such unusual and challenging conditions, operators need to rely both on knowledge acquired through training and experience, and on appropriate decision support tools. These tools must be designed to leverage a new wealth of data and algorithmic techniques while being mindful of the cognitive limitations of the human users.
People
  • Alexandra von Meier
    Director, Electric Grid Research, CIEE
  • Mohini Bariya
    Graduate Student Researcher, UC Berkeley
  • Anurag Srivastava, Paul Whitney, Anjan Bose, Adam Hahn, Saeed Lotfifard
    Washington State University
  • Gautam Biswas, Abhishek Dubey
    Vanderbilt University
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This project aims to assist operators during challenging and rare grid events through novel decision support tools and improved, data-driven training. This project will build advanced, machine learning based tools to fit into an adaptive human-machine system and improve existing training simulators to incorporate such tools and more data.

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