An Online Power System Dynamics Prediction Based on Deep Neural Network

Abstract

Building Power analysis has drawn more and more attention in recent years. In this paper, we present a system for online power prediction for the public building. It is based on a 4-layers Deep Neural Network that use architectural metrics of the physical machines collected dynamically by our system to predict the physical machine power consumption. A real implementation of our system shows that the prediction accuracy could reach 76.50%.