Comparison of peak load predictions and treatment of solar gains in the admittance and heat balance load calculation procedures

Abstract

Calculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE-CIBSE research project to compare design cooling calculation methods. Peak cooling loads predicted by the ASHRAE heat balance method are compared with those predicted by a number of implementations of the admittance method using different window models. The results presented show the general trends in overprediction or underprediction of peak load. Particular attention is given to different window modelling practices. The performance of the methods is explained in terms of some of the underlying assumptions in the window models, and by reference to specific inter-model comparisons.

Comparative Analysis of CIBSE Admittance and ASHRAE Radiant Time Series Cooling Load Models

“…Chartered Institution of Building Services Engineers (CIBSE) and American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) methods are widely adopted globally for cooling load calculation [9]. In terms of calculation method, CIBSE adopts the admittance method, which is based upon the fundamentals of heat transfer and the calculation procedures being simplified to be able to deal with both steady-state and fluctuating loads [10]. The ASHRAE, on the other hand, uses radiant time series (RTS) to calculate steady-periodic cooling loads, which are processed by splitting the heat gain components into convective and radiant components [11].…”

“…Spitler et al [13] demonstrated a slight overprediction using the RTS method that lead to significantly higher prediction on buildings with a high window-to-wall ratio. On the other hand, the CIBSE admittance method of using the solar gain factor-based window model underpredicts cooling loads [10]. Large window areas may result in excessive solar gains and thus require huge amounts of cooling power [18].…”

“…In fact, the CIBSE's method relies on tabulated data to determine time lags, resulting from correction factors related to the fabric's properties [19]. This is seen for heavy or lightweight buildings that use simplistic correction factors, and may not provide a precise result in cooling loads due to the vague associated time lags [10]. Brembilla et al [20] report that part of the inaccuracy is due to cloud coverage being measured by automated ceilometers.…”