Supervisory Control for Resilient Chiller Plants Under Condenser Fouling

• Published in: IEEE access Vol. 5; pp. 14028 - 14046
• Main Authors: Mittal, Khushboo, Wilson, James P., Baillie, Brian P., Gupta, Shalabh, Bollas, George M., Luh, Peter B.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-01-2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Buildings; chiller plants; Chillers; Computational efficiency; Condenser tubes; Cooling; Cooling loads; Discharge; Energy consumption; Energy efficiency; Fault detection; Fault diagnosis; Fault tolerance; Fault tolerant systems; Fouling; fouling diagnosis; Life expectancy; Maintenance engineering; Mass flow rate; Parameters; Resilience; Resilient control; sensor selection; Strategy; Supervisory control
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2017.2726017

This paper presents a supervisory control strategy for resilient chiller plants in the presence of condenser fouling. Fouling results in off-nominal performance of chiller parameters, such as increased refrigerant mass flow rate, compressor motor speed, discharge pressure, and discharge temperature. These effects further lead to faster deterioration of condenser pipes and tubes, and increase the risk of early motor failures. Thus, the main objective of this paper is to provide resilience, i.e., to bring the system parameters back to normalcy, and thereby protect the system from the adverse effects of fouling and improve its life expectancy while ensuring energy efficiency and meeting the desired cooling load. The supervisory control strategy presented here incorporates fault detection and diagnosis (FDD) and resilient control for mitigating the effects of condenser fouling. A computationally efficient and robust FDD scheme enables the estimation of the condenser fouling level using optimal sensor selection and statistical classifiers, thus facilitating condition-based maintenance. On the other hand, the resilient control scheme enables redistribution of load between chillers in order to reduce the load on faulty equipment in an energy-efficient manner, while still providing the required overall cooling load. The performance of this method is tested and validated using a high-fidelity chiller plant model and the proposed strategy is shown to diagnose condenser fouling with a high accuracy and effectively mitigate the effects of fouling at low computational cost. It is shown that the supervisory controller is able to meet the desired building load requirements at lower energy consumption, as compared with no supervisory control.