Assessment of operating performance of chiller systems using cluster analysis

Abstract

This study assesses the operating performance of chiller systems by using cluster analysis. Cluster analysis is a statistical tool used to identify groups of individuals similar to each other but different from individuals in other groups. This serves the purpose of classifying what operating condition constitutes a high or low system coefficient of performance (COP). A system with five chillers of two different cooling capacities has been studied. Seven typical operating variables for each chiller were monitored at half-hour intervals over a year. After dividing around 17,000 sets of operating data into five cluster groups by the two-step cluster analysis, it is possible to identify the sensitivity of system COP to each operating variable and, in turn, to prioritize the critical variables influencing the system COP. The significance of this study is to demonstrate a systematic method to rank operating variables according to their influence on the COP of any given chiller system and hence to improve settings of the controllable variables to increase the COP.