Major
Computer Engineering
Anticipated Graduation Year
2023
Access Type
Open Access
Abstract
The research evaluates various computational methods to improve the efficiency of power grid operations. The objective is to design an algorithm that improves the efficiency of power grids by controlling the operation of the voltage regulators and power converters. Using a real-time communication with distributed sensors and evolutionary artificial neural networks, the method could reveal the presence of disturbances and provide configurational changes that improve the system stability.
Faculty Mentors & Instructors
Dr. Brook Abegaz, Department of Engineering
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Improving the Stability of Smart Power Grids Using Evolutionary Neural Networks
The research evaluates various computational methods to improve the efficiency of power grid operations. The objective is to design an algorithm that improves the efficiency of power grids by controlling the operation of the voltage regulators and power converters. Using a real-time communication with distributed sensors and evolutionary artificial neural networks, the method could reveal the presence of disturbances and provide configurational changes that improve the system stability.