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Grid Operator Assessment and Training (GOAT)

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0021757
Agency Tracking Number: 0000268295
Amount: $1,099,994.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: C52-07b
Solicitation Number: N/A
Timeline
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-08-22
Award End Date (Contract End Date): 2024-08-21
Small Business Information
2900 S MAIN ST
SALT LAKE CITY, UT 84115-3516
United States
DUNS: 013017947
HUBZone Owned: Yes
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Larry Sadwick
 (801) 975-7399
 sadwick@innosystech.com
Business Contact
 Larry Sadwick
Phone: (801) 975-7399
Email: sadwick@innosystech.com
Research Institution
N/A
Abstract

Statement of the problem or situation that is being addressed throughout Phase I portion of your proposal: Training power-grid operators for public utilities has proven difficult. Many trainees fail to learn quickly enough to graduate from Operator training. Despite relatively high salaries, many trainees who graduate are relatively quickly hired away from public utilities by better-paying jobs in the private sector. Public utilities need a better training pipeline for Load Operators
General statement of how this problem is being addressed: To develop a better training pipeline, InnoSys is applying simulation-based Learning-by-Doing training to Load Operators. This approach efficiently trains people who must understand complex systems in order to resolve faults with unexpected symptoms arising from never-before-experienced situations. Learning by doing exploits the advantages of training within a simulation in a variety of ways. First, training is conducted within the situation in which the knowledge is used—trainees not only learn how the system works, but when specific types of knowledge should be applied. Second, training requires trainees to practice thinking how to solve problems within a context that is similar to their job. If they need help to solve the problem, rather than being told the resolution, they are given hints and use them to resolve the situation—trainees construct their knowledge as they resolve problems. Third, training is constructed to minimize cognitive overload as trainees solve problems--for example, first trainees focus on solving the problem; then they focus on lessons learned.
What was done in Phase I: In Phase I, we identified an existing, commercially proven simulation of the power grid to enhance with our training enhancements. We tested and refined methods to capture expertise from experienced, and improve trusted Operators. The expertise was used to design an assessment system which yielded a score of overall performance and identified performance weaknesses. The expertise was also used to design instructional interactions to improve trainee performance and knowledge.
What is planned for the Phase II project: We will apply Learning by Doing by creating scenario- based training for (1) load operators facing power outages after natural disaster and (2) unemployed workers who are considering changing careers to become load operators. Both of these training packages will be developed and deployed with refinement from collaborating utilities, tested for effectiveness, and then made commercially available.
Commercial Applications and Other Benefits: Commercialization success of our Experiential Load Operation Trainer will require that decision makers who select training must pay attention to (1) the metrics that show the advantages of Learning by Doing, (2) inspecting the instruction and appreciating its advantages, and/or (3) testimonials from students and experts who have observed how effectively it trains. Our commercialization approach is to license our technology and courses to companies that already sell training to power-grid training companies. The training methods developed and tested can be applied much more broadly within the power industry and more broadly to utilities and manufacturing industry sectors. Currently, the market size for operator training via simulation is slightly over $11B. The CAGR for the next 4 years is projected to be about 12.5%. The market size for simulator training for operators will approach $20B.

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

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