Analysis of Air Conditioning Effectiveness vs. Outdoor Conditions: Traditional Bins or Joint Frequency Bins?

Abstract

There are a number of methods used to estimate the effectiveness of air conditioning equipment in handling loads. Full hourly computer simulations are probably the most accurate, but lack flexibility and are more cumbersome to use than more compact approaches. Alternately, some form of binned weather data has been used with load and performance estimation carried out for each of the bin weather conditions. The most common binning method puts weather into bins of dry bulb temperature with mean coincident wet bulb temperatures. Mean coincident humidity terms lose the extreme humidity levels that commonly exist. This can lead one to assume that conditions will be held at all times, while in fact the humidity loads will not be met and discomfort, among other consequences, will result. Three-dimensional plots of the joint frequency results clearly illustrate problem areas. A better procedure, it will be shown, is to use a joint frequency bin data set, which puts hours of occurrence into a matrix with dry bulb ranges on one axis and humidity ratio ranges on the second axis. This form of binning is easily accomplished if a utility like BinMaker is used to generate the binned data set.