Survey and Artificial Neural Network Analysis on Occupant's Household Energy Use in a High-Rise Multi-Unit Residential Building in Toronto, Canada

Examining occupant's household energy use is a crucial step in achieving significant reductions in energy consumption. The purpose of this thesis is to collect information on ownership of appliances and electronics to evaluate their use, energy consumption, and behaviour with respect to energy in a Toronto high-rise multi-unit residential building (MURB). In this thesis, a survey was developed and implemented in a Toronto high-rise MURB. The survey data, energy consumption data from October 2010 to September 2012, and weather conditions were analyzed and used to develop an artificial neural network (ANN) model. The detailed analysis of survey data resulted in the development of relationships between occupant's demographics and energy consumption. By creating an ANN model, results showed that the implementation of the survey may have reduced occupant's energy consumption in the high-rise MURB.