This PFI: AIR Technology Translation project focuses on translating a neural network vector control technology to fill the need for renewable and smart grid control and integration. The technology is important because it will improve the power quality and facilitate an uninterrupted energy supply, increase incentives for consumers to use energy from renewable resources and electric vehicles, and accelerate progress towards America's target of deriving 20% of its electrical energy from renewable resources by 2030. The project will result in a prototype of a grid-connected power converter using the neural network vector control technology. This technology has the following unique features: fast response time, low overshoot and close to ideal control performance. These features provide the advantages of improved efficiency, reliability, stability and power quality of an electric utility system with integrated renewables as compared to the leading competing conventional standard vector control technology in this market space.

This project addresses the following technology gaps as it translates from research discovery toward commercial application: (1) proving the concept of the neural network control technology for grid-connected converters that meets the needs of electric power systems, (2) demonstrating a functional prototype power converter board that uses neural network control to integrate renewables into smart grids, (3) evaluating and benchmarking a commercially valuable solution of neural network control against conventional technology, and (4) developing a strategy for commercialization beyond this project. In addition, personnel involved in this project, PIs, undergraduates and graduates, will receive innovation translation experiences through activities from technical and business perspectives. The team of students, along with the PI, will participate in the Crimson Startup Canvas, UA's customer discovery program to understand the formal process through which to identify sustainable business models, increase the chance of attracting funding and investments, create new jobs and benefit society.

The project engages Southern Company Services to participate in an advisor role, offer guidance for the project, and guide commercialization aspects in this technology translation effort from research discovery toward commercial reality.

Project Start
Project End
Budget Start
2014-09-15
Budget End
2017-08-31
Support Year
Fiscal Year
2014
Total Cost
$217,780
Indirect Cost
Name
University of Alabama Tuscaloosa
Department
Type
DUNS #
City
Tuscaloosa
State
AL
Country
United States
Zip Code
35487