Philip Haves
Zitiert von
Zitiert von
Model predictive control for the operation of building cooling systems
Y Ma, F Borrelli, B Hencey, B Coffey, S Bengea, P Haves
IEEE Transactions on control systems technology 20 (3), 796-803, 2011
On approaches to couple energy simulation and computational fluid dynamics programs
Z Zhai, Q Chen, P Haves, JH Klems
Building and Environment 37 (8-9), 857-864, 2002
Analysis of an information monitoring and diagnostic system to improve building operations
MA Piette, SK Kinney, P Haves
Energy and Buildings 33 (8), 783-791, 2001
A framework for simulation-based real-time whole building performance assessment
X Pang, M Wetter, P Bhattacharya, P Haves
Building and Environment 54, 100-108, 2012
Advanced sensors and controls for building applications: Market assessment and potential R&D pathways
MR Brambley, P Haves, SC McDonald, P Torcellini, D Hansen, ...
EERE Publication and Product Library, Washington, DC (United States), 2005
Peak demand reduction from pre-cooling with zone temperature reset in an office building
P Xu, P Haves, MA Piette, J Braun
A modular building controls virtual test bed for the integrations of heterogeneous systems
M Wetter
Efficient solution strategies for building energy system simulation
EF Sowell, P Haves
Energy and buildings 33 (4), 309-317, 2001
SinModel: a domain data model for whole building energy simulation
J O'Donnell, R See, C Rose, T Maile, V Bazjanac, P Haves
An experimental study of air flow and temperature distribution in a room with displacement ventilation and a chilled ceiling
SJ Rees, P Haves
Building and Environment 59, 358-368, 2013
Condition monitoring in HVAC subsystems using first principles models
P Haves, TI Salsbury, JA Wright
© American Society of Heating, Refrigerating and Air-Conditioning Engineers …, 1996
Application of machine learning in the fault diagnostics of air handling units
M Najafi, DM Auslander, PL Bartlett, P Haves, MD Sohn
Applied Energy 96, 347-358, 2012
Model-based real-time whole building energy performance monitoring and diagnostics
Z O’Neill, X Pang, P Haves, M Shashanka, T Bailey
Automated Diagnostics and Analytics for Buildings, 205-225, 2021
Modeling and simulation of HVAC faults in EnergyPlus
X Basarkar, Mangesh, Pang, L Wang, P Haves, T Hong
A nodal model for displacement ventilation and chilled ceiling systems in office spaces
SJ Rees, P Haves
Building and Environment 36 (6), 753-762, 2001
Strategies for coupling energy simulation and computational fluid dynamics programs
Z Zhai, Q Chen, JH Klems, P Haves
Comparison of chiller models for use in model-based fault detection
P Sreedharan, P Haves
A standard simulation test bed for the evaluation of control algorithms and strategies
P Haves, LK Norford, M DeSimone
ASHRAE transactions 104, 460, 1998
A robust self-tuning predictive controller for HVAC applications
AL Dexter, P Haves
ASHRAE Transactions (American Society of Heating, Refrigerating and Air …, 1989
Towards a very low-energy building stock: modelling the US commercial building sector to support policy and innovation planning
B Coffey, S Borgeson, S Selkowitz, J Apte, P Mathew, P Haves
Building Research & Information 37 (5-6), 610-624, 2009
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