Paper: Improving the Accuracy of Building Energy Simulation Using Real-Time Occupancy Schedule and Metered Electricity Consumption Data <span>(LB-17-C033)</span> (2017 ASHRAE Annual Conference)

2 Improving the Accuracy of Building Energy Simulation Using Real-Time Occupancy Schedule and Metered Electricity Consumption Data (LB-17-C033)

Chandra Sekhar, Ph.D., National University of Singapore

Junjing Yang, Ph.D., National University of Singapore

Prashant Anand, National University of Singapore

David Cheong, Ph.D., National University of Singapore

Occupancy plays a significant role in the amount of energy used in buildings and their presence is stochastic in nature. There is extensive evidence to suggest that buildings usually do not perform as well as predicted by energy simulation. Use of unrealistic occupancy data as an input of building energy modelling (BEM) is a major reason behind it. As a result, large discrepancies are being observed between predicted and actual energy performance, typically averaging around 30% and reaching as high as 100% in some cases. This paper covers research that aims to develop an occupancy prediction model using Artificial Neural Network (ANN) for improving the accuracy of building energy simulation.

See more of: Using Occupancy and Actual Short-Term/Long-Term Energy Data to Develop More Accurate Modeling Tools