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Machine Learning for Optimized Chiller Staging

06-15-2017 13:08

Summary

Owners of campus cooling plants with multiple units typically run more efficient chillers as often as possible and minimize run hours on the least efficient units. However, this doesn’t always deliver peak efficiency. Ben Erpelding will discuss how machine learning can deliver greater efficiencies and is challenging best-practice operational strategy. He will cover the supporting data science and present a CS in which this method was implemented on a plant with 12 identical 1,850-ton chillers.

Speaker

Ben Erpelding, Optimum Energy



#OptimumEnergy #EnergyEfficiency #2017 #ConferenceProceeding #CampusEnergyConference #NorthAmerica #ChilledWater #Optimization #Chillers #DistrictCooling

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Machine Learning for Optimized Chiller Staging   1.15MB   1 version
Uploaded - 06-15-2017
Ben Erpelding, Optimum Energy