Daniel Holcomb and Wenchao Li and Sanjit A. Seshia

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2009-138

October 15, 2009

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-138.pdf

We consider two problems in the design and operation of energy-efficient buildings. The first is the prediction of energy consumption of a building from that of similar buildings in its geographical neighborhood. The second problem concerns the localization of faults in building sub-systems with a focus on faults that lead to anomalous energy consumption. For both problems, we propose algorithmic techniques based on machine learning to address them. Simulation results using EnergyPlus show the promise of the proposed methods.

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BibTeX citation:

@techreport{Holcomb:EECS-2009-138,
    Author= {Holcomb, Daniel and Li, Wenchao and Seshia, Sanjit A.},
    Title= {Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis},
    Year= {2009},
    Month= {Oct},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-138.html},
    Number= {UCB/EECS-2009-138},
    Abstract= {We consider two problems in the design and operation of energy-efficient buildings. The first is the prediction
of energy consumption of a building from that of similar buildings in its geographical neighborhood. The second
problem concerns the localization of faults in building sub-systems with a focus on faults that lead to anomalous
energy consumption. For both problems, we propose algorithmic techniques based on machine learning to address
them. Simulation results using EnergyPlus show the promise of the proposed methods.},
}

EndNote citation:

%0 Report
%A Holcomb, Daniel 
%A Li, Wenchao 
%A Seshia, Sanjit A. 
%T Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis
%I EECS Department, University of California, Berkeley
%D 2009
%8 October 15
%@ UCB/EECS-2009-138
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-138.html
%F Holcomb:EECS-2009-138