A Novel Application to Increase Energy Efficiency Using Artificial Neural Networks - Büyük, Oğuzhan Oktay; Bilgin, Sevgi Nur (IEEE, 2016)
In this paper, a novel system application to recover electricity losses using an unsupervised learning, self-learning mapping mechanism is introduced. Actually, energy and its transmission are becoming a vital issue for both the economy and the environment. Considering many devices in our world run on electricity, it is now important to keep up with how we can obtain maximum energy efficiency in electricity transmission by reducing losses and leakage. A new system application and module approach can communicate with electricity transmission lines to define and track energy losses. In this study, we examine how the system uses unsupervised learning to find the best transmission path to follow. This application is designed to interconnect with electricity transmission line on smart grids. This system also has critical recovering on CO2 emissions occurring on routing correct plan, notification integration which may prepare a report to the network nodes by itself.
Keywords: Artificial Neural Networks; Istributed Energy Management; Energy Efficiency; Unsupervised Learning