Probabilistic approach to determination of internal heat gains in office, building for peak load calculations

We propose a methodology for determining internal heat gains in workspace for peak cooling/heating load calculations. First, we collected measurement data of the lighting and plug loads in workspaces in Japan and analyzed these data. The investigation results show that internal heat gains remain relatively flat during work hours for each space, but their magnitudes vary considerably from space to space. Time-averaged heat gains during work hours conform to a lognormal distribution if those spaces are approximately the same size in floor area. Next, we present a methodology to determine the value of heat gains at specified frequencies of occurrence for each space. We present detailed procedures to calculate the probabilistic distributions with the Markov chain Monte Carlo method in conjunction with the Bayesian approach and analyze the calculation results by using the measured data. Finally, we discuss the applicability of the proposed stochastic approach.