Fault Detection and Diagnosis for Thermal Energy Storage HVAC System

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The objective of this research project is the optimum operation of HVAC system having thermal energy storage without any faults. In order to realize the fault detection and diagnosis, the performance indices of storage operation, the tool for fault detection and diagnosis and the optimum operation with computer simulation were studied. The following is the summary of the obtained results.1. The indices for the peak shift and peak cut operations were presented to evaluate the operation condition in actual systems. And, the usefulness of these indices were validated by using the measured data in actual systems.2. An expert system was constructed by combining the fuzzy abduction algorithm for fault detection and diagnosis with knowledge database for reasons and symptoms of faults. And, the effect of the membership function on the obtained diagnosis result was studied.3. The model parameters of physical models for chiller and air-handling unit in thermal energy storage system were identified from the measured data in actual systems. And, these models were combined with the mixing model of water tank for thermal energy storage, and a computer program allowing to simulate the operation condition was built up as a tool for cost/benefit analysis of fault improvement.4. The temperature profile in water tank was predicted by using the mixing model of water tank and the measured data. And, by convergence calculation to obtain the minimum error of the predicted temperature profile, the flow rate through the water tank, chillers and air-handling units were estimated as well as the characteristics of chillers and air-handling units in actual systems. This procedure was found to allow to simulate the operation condition accurately without any physical models for chillers and air-handling units.