Sponsor(s)
National Science Foundation
Contributor(s)
Andreas Spanias
Jie Fan
Vivek Narayanaswamy
Sameeksha Katoch
Remote Video
Submitted by Andreas Spanias on August 27th, 2021
Submitted by Andreas Spanias on June 7th, 2021
Submitted by Andreas Spanias on April 9th, 2020
We describe a Cyber-Physical system approach to Photovoltaic (PV) array control. A machine learning and computer vision framework is proposed for improving the reliability of utility scale PV arrays by leveraging video analysis of local skyline imagery, customized machine learning methods for fault detection, and monitoring devices that sense data and actuate at each individual panel. Our approach promises to improve efficiency in renewable energy systems using cyber-enabled sensory analysis and fusion.
Submitted by Pavankumar Tallapragada on January 22nd, 2019
In this paper, we describe a Cyber-Physical system approach to Photovoltaic (PV) array control. A machine learning and computer vision framework is proposed for improving the reliability of utility scale PV arrays by leveraging video analysis of local skyline imagery, customized machine learning methods for fault detection, and monitoring devices that sense data and actuate at each individual panel. Our approach promises to improve efficiency in renewable energy systems using cyber-enabled sensory analysis and fusion.
Submitted by Andreas Spanias on November 29th, 2017
Submitted by Andreas Spanias on November 15th, 2017