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PROACTIVE ENERGY MANAGEMENT FOR NEXT-GENERATION BUILDING Victor M. Zavala1, Jianhui Wang2, Sven Leyffer1
 

Summary: PROACTIVE ENERGY MANAGEMENT FOR NEXT-GENERATION BUILDING
SYSTEMS
Victor M. Zavala1, Jianhui Wang2, Sven Leyffer1
Emil M. Constantinescu1, Mihai Anitescu1, and Guenter Conzelmann2
1Mathematics and Computer Science Division
2Decision and Information Sciences Division
Argonne National Laboratory, 9700 S Cass Ave, Argonne, IL 60439
ABSTRACT
We present a proactive energy management framework
that integrates predictive dynamic building models and
day-ahead forecasts of disturbances affecting efficiency
and costs. This enables an efficient management of re-
sources and an accurate prediction of the daily electricity
demand profile. The strategy is based on the on-line solu-
tion of mixed-integer nonlinear programming problems.
The framework is able to integrate forecasts of weather
conditions, fuel prices, heat gains, and utility demands.
In addition, it can capture net-metering interactions us-
ing agent-based market models. We claim that a large
adoption level of this proactive technology can improve

  

Source: Anitescu, Mihai - Mathematics and Computer Science Division, Argonne National Laboratory
Argonne National Laboratory, Mathematics and Computer Science Division (MCS)

 

Collections: Computer Technologies and Information Sciences; Mathematics