 Deep neural networks, DNN, are specifically investigated in this article for energy demand forecasting at the individual building level. The results of the experiment using the proposed method show that it is possible to predict 98.1%, grow at 96.8%, meet 98.5% of electricity demand, use 97.6% of power, and have a renewable energy ratio of 96.2%. This article was authored by Mingming Wen, Changsha Zhou, and Maminov Konstantin.