Ludwig Lechtreck & Michael Tang

The increasing demand for sustainable and energy-efficient buildings has created a need to predict energy consumption. Often it is difficult to predict the precise impact of various energy efficiency improvements. Ever-changing weather conditions make it even more difficult to assess such impacts. In our Hacklytics submission, we present a solution for predicting the energy consumption of a building over a month-scale. Our approach uses machine learning algorithms and building performance data to estimate the energy consumption of a building with high accuracy.