Estimation of Energy Savings for Building Retrofits Using Neural Networks

Abstract

This paper overviews some applications of neural networks (NNs) to estimate energy and demand savings from retrofits of commercial buildings. First, a brief background information on NNs is provided. Then, three specific case studies are described to illustrate how and when NNs can be used successfully to determine energy savings due to the implementation of various energy conservation measures in existing commercial buildings.