Research on building electricity saving by 65% base on BPNN

With the development of building materials and the increase of the energy efficiency ratio of air conditioner, building electricity saving by 65% has been taken into consideration. In this study, the main objective is to predict buildings electricity consumption potential of building envelope performance parameters and to determine the measures to building electricity saving by 65% by using BP neural networks. A three-layered BPNN was modeled and BPNN toolbox of MATLAB was used for predictions. Results show that BPNN gives satisfactory outputs with successful prediction rate of over 98% and provides the energy efficient measure to reach building electricity saving by 65%.