Applying grey forecasting to predicting the operating energy performance of air cooled water chillers

Abstract Grey forecasting has found applications in finance, social science, economics, etc. However, its applications in air conditioning and refrigeration have not been reported. This paper reports on a study where grey forecasting method is applied to predicting the operating energy performance for an air cooled water chiller (ACWC) units, so as to demonstrate this forecasting approach can be applied to building Heating Ventilation and Air Conditioning (HVAC) installations. In this paper, a brief introduction of the background and fundamentals of grey forecasting is firstly presented. This is followed by reporting the application of grey forecasting to an ACWC unit installed in Northern China for predicting its operating energy performance using the variation ratio of coefficient of performance (ΔCOP). The predicted values of ΔCOP agreed well with the measured ΔCOP, demonstrating that grey forecasting may be used for predicting the operating energy performance of an ACWC unit with a high accuracy. Finally, the potential use of grey forecasting in fault detection and diagnostics (FDD) or energy management systems (EMSs) for air conditioning and refrigeration systems is assessed, and the comparison with the prediction method based on artificial neural network (ANN) discussed.