This paper focuses on experimental evaluation and verification of model free extremum seeking control, a real-time gradient descent optimization tool. There have been several publications illustrating the effectiveness of extremum seeking control applied to a variety of heating, ventilation, and air conditioning plants in simulation and on mini - split ductless air conditioning system test beds. However, possibly due to inaccessibility of commercially operational chiller plants for experimentation, an evaluation of extremum seeking has not been documented for a large scale in-service building chiller plant. In this paper, a single input extremum seeking control approach is applied to a 2200RT commercial building chiller plant at Chinatown Point mall in Singapore. The extremum seeking control algorithm selects a set point for the condenser water pump flow rate in order to find the value that minimizes the chiller plant's energy consumption. Evaluation experiments took place over a testing period lasting 5 week days and cycling through morning, daytime, evening, and night modes of operation. Results show that extremum seeking achieves as much as a 1.5% efficiency increase in comparison to a constant-input approach tuned by an expert chiller plant automation engineer; performance improvement is greatest in the off nominal mode where 3 chillers are running than in the nominal mode where 4 chillers are running.
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