An occupant-based energy consumption prediction model for office equipment

Abstract

Occupant energy demand plays an important role in whole building energy consumption. To improve building energy efficiency, the stochastic characteristics of occupant behavior should be explored. In this paper, an occupant-based energy consumption prediction model was proposed based on the analysis of the relationship between occupant behavior and equipment energy consumption, drawing from an indoor occupancy rate model and computer input power model. Polynomial and Markov chain–Monte Carlo methods were applied to describe the time-varying indoor occupancy rate and the computer input power in multi-occupant office rooms. The computer energy consumption and occupant activity were related through the time-varying indoor occupancy rate. The energy consumption of office equipment was calculated by time accumulation and necessary correction. Three office buildings with different functions were selected as case studies, which are mainly used for business, administration and scientific research. The error rate between the predicted energy consumption from the model and actual energy consumption record was below 5%.