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Eye Tracking Assisted Human Factor Analysis Platform for Power System Situational Awareness

Data presentation techniques in power grid operations are important in determining situation awareness for control room engineers and operators. While innovative displays can be designed to convey static, dynamic, and other relevant attributes of grid information, an arising concern is their effectiveness in enabling control room operations. This paper presents an integrated architectural platform for performing human factors experimenting and analysis for power systems situation awareness. It leverages eye-tracking and other biosensing devices in simulated power system operations to capture critical human behavior data that can be further analyzed to extract qualitative and quantitative metrics in defining grid situation awareness. The architecture is designed to enable the assessment of presentation techniques and behavior of users (otherwise, known as respondents) either in real-time simulated grid operations, or offline when conveying the current state of the grid through static displays.