Practically feasible and novel approach for predicting electrical power demand of multiple dwellings using a digital tool in building services industry

This study aims to provide a novel and practical methodology for simulating the electrical power demand (EPD) in buildings. In design stage, estimation of the EPD is largely based on previous experience of an engineer, and often the EPD is overestimated to ensure continuous electrical power supply. However, overestimated EPD would results with oversized services and associated increase in greenhouse gas emissions.

In this study, an existing occupancy driven bottom-up stochastic modelling tool validated by field data for predicting the EPD of a single household for a single-day was modified to predict the EPD of multiple households with various sizes for a specified duration. Furthermore, the results were processed using a Monte Carlo analysis to cover a wide range of possible scenarios. It is expected that the novel methodology would be invaluable to stakeholders for making informed decisions resulting with significant savings in associated constructions costs and building carbon emissions.