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Intelligent Utility Operator Training Platform

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0021757
Agency Tracking Number: 0000259786
Amount: $199,999.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 07b
Solicitation Number: N/A
Timeline
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
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 Sacwick
 (801) 975-7399
 sadwick@innosystech.com
Business Contact
 Larry Sadwick
Phone: (801) 975-7399
Email: sadwick@innosystech.com
Research Institution
N/A
Abstract

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. 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. In Phase I, we will first refine methods to capture expertise from experienced, trusted Operators. This will form the basis of the training. Second, we will construct a prototype Learn-by-Doing environment. Experts, trainees, and DOE staff can observe how this training will help learners. Third, as users interact with the prototype, we will obtain feedback on training effectiveness. 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 who have experienced Learning by Doing and experts who have observed how effectively it trains. 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. Our commercialization approach is to license our technology and courses to companies that already sell training to power-grid training companies.

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

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