Estimation of Total Energy Load of Building Using Artificial Neural Network

This paper explores total heat load and total carbon emissions of a six storey building by using artificial neural network (ANN). The energy performance in buildings is influenced by many factors such as ambient weather conditions, building structure and characteristics, the operation of sub-level components like lighting and HVAC systems, occupancy and their behavior. This complex situation makes it very difficult to accurately implement the prediction of building energy consumption. The calculated total load was 2.09 million kW per year. ANN application showed that data was best fitted for the regression coefficient of 0.99812 with best validation performance of 1312.5203 in case of total heat load. To meet out this energy demand fuel options are presented along with their cost and carbon emission and necessary measures has been given.