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Externalized Decision-Making User Interface for Training Smart Grid Operators

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0021841
Agency Tracking Number: 0000259287
Amount: $200,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 07b
Solicitation Number: N/A
Solicitation Year: 2021
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-06-28
Award End Date (Contract End Date): 2022-03-27
Small Business Information
9180 Brown Deer Road
San Diego, CA 92121-2238
United States
DUNS: 131182388
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Cory Rieth
 (858) 535-1661
Business Contact
 Ronald Moore
Phone: (858) 535-1661
Research Institution

Modern power grid technologies have helped meet increasing energy demands and prepare for the future but have also added to the complexity of the system and training required of grid operators. Modern grid operators must learn how to monitor and manage the grid to prevent surges and outages, in addition to making wildfire risk mitigation decisions, as effectively and efficiently as possible. Current training is time-consuming, lags technology development, is insufficiently responsive to environmental drivers for change (e.g., increasing need for emergency response), and is often mismatched to a scientific understanding of how people actually learn. The project team proposes to research, develop, and demonstrate an externalized decision-making user interface for training, taking the form of an array of smart training solutions tailored to the tasks and decision-making needs of modern grid operators. These training solutions will be based on the application of a Learning Approach Matrix that aligns training approaches, content, training vignettes, and schedules with the specific end user needs of grid operators. Additionally, our proposed training solutions will leverage and extend a flexible user interface concept that externalizes user interpretation of data and can be used to understand how experts and trainees interpret data differently, providing awareness of difficult to articulate expert decision processes and feedback for trainees. In Phase I, a tailored user-centered design process to develop innovative training solutions to support modern grid operator will be employed. This process will be used to identify training needs of representative grid operator trainers and trainees from a local utility company strongly endorsing this effort, determine the challenges related to grid operator training, design, develop, and assess the technical feasibility of the proposed training solutions, and secure endorsement of this work for modern grid operator training. In Phase II, the project team will develop a data-driven, working prototype of the training solutions for transition to a local utility company, and potentially training vendors, for implementation, testing, and refinement. The training solutions developed in this project will help streamline the training process to better meet the needs of grid operators and, ultimately, support safer, more reliable operation of the modern power grid.

* Information listed above is at the time of submission. *

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