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Optimization through the Perfect Plant Design

Summary Optimum Energy will be presenting on chilled water system optimization and methods to enhance traditional variable speed controls through sustainable design best-practices. Achieving peak system operational performance is a journey that starts at plant design and is maintained through...

3C.3_Toback.pdf


Library Entry
Machine Learning to Facilitate District Energy System Optimization: A Pharmaceutical Case Study

Summary How do you effectively optimize cooling loads in district-scale energy systems? Current algorithm-based optimization solutions are effective, but they require site-specific customization. The ideal solution incorporates integrated machine learning, which enables algorithms to improve...

1C.2_Dempster.pdf


Library Entry
UT Austin Optimization Journey

Summary The story of how UT Austin built a first class operation with highest reliability, highest efficiency, and highest level of service. Speaker Michael Manoucheri, University of Texas-Austin Ben Erpelding, Optimum Energy #UniversityofTexasAustin #CampusEnergyConference ...

Wkshop2_8MANOUCHERIERPELDING.pdf


Library Entry
Finding energy saving opportunities on a large scale University Campus: How the University of Texas strategically selects energy optimization projects

Summary The University of Texas contains over 130 buildings. With so many buildings, where do you focus your energy? Learn how the University of Texas selects projects that optimize campus resources and maximize energy efficiency. We will explain how we select the best approach based on a...

2C.1_Berens_Erpelding_Isakson.pdf


Library Entry
Optimizing the Building Side of District Cooling

Speakers Eric Toback, Optimum Energy #Workshop #CoolingConference #OptimumEnergy #2016 #ConferenceProceeding #MeteringandControls #Optimization #DistrictCooling

TobackEric.pdf


Library Entry
Machine Learning for Optimized Chiller Staging

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...

5D.4_Erpelding.pdf