Energy Consumption Prediction in Low Energy Buildings using Machine learning and Artificial Intelligence for Energy Efficiency

Abstract

Load forecasting is one of the most important step to maintain demand-supply balance and stability in a power system. With the advent of artificial intelligence and machine learning tools, load forecasting/energy consumption prediction is conducted with increased accuracy. The application of several machine learning techniques to predict energy consumption has been reported. However, a detailed analysis of different techniques is beneficial to choose the right approach to specific cases. This paper presents a study of different prediction models in energy forecasting. The prediction models are implemented in Matlab. The training and testing results for the data set is presented.