Energy efficient operation based on root cause analysis for multiple-chiller plant

In large gas district cooling plant, chillers´ performance bottleneck analysis is important not only for anomaly detection, but also for energy optimal operations. Currently many researches adopt linear or non-linear regression correlation analysis methods to detect chiller´s bottleneck, however their works majorly focus on single chiller´s anomaly factors analysis, which cannot be directly applied on operation optimization especially in large multiple-chiller plant, because single-chiller model cannot answer the questions of when and where the plant level´s bottleneck happens. The present paper extends single-chiller anomaly analysis model RCA into a multiple-chiller oriented performance root cause analysis model RCA+, designs two energy optimal steam operation algorithms to meet cooling demand´s rising and lowering, and verifies the algorithms´ energy saving effectiveness by simulation. The simulation result shows that proposed optimal operation algorithms can implement about 11.6% higher steam efficiency than COP-based method for studied multiple-chiller plant.