A comparison of thermal zone aggregation methods

Dobbs, Justin R.; Hencey, Brandon

doi:10.1109/cdc.2012.6425888

Cited by 6 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model used for this study has 41 states: one for zone air and the rest for building structure 3 . It assumes well-mixed air and uses time-invariant convection coefficients.…”

Section: Building Thermal Modelmentioning

confidence: 99%

“…In practice, one may reduce the model size using balanced truncation, which reconfigures the state space. We have chosen to retain the full-order model to maximize accuracy and preserve physical intuition.See[3] for a survey of methods that reduce state space size while preserving structure 4. Daily ground temperature is available for free through on-line sources such as the U.S.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Model predictive HVAC control with online occupancy model

Dobbs

Hencey

2014

Energy and Buildings

Self Cite

View full text Add to dashboard Cite

a b s t r a c tThis paper presents an occupancy-predicting control algorithm for heating, ventilation, and air conditioning (HVAC) systems in buildings. It incorporates the building's thermal properties, local weather predictions, and a self-tuning stochastic occupancy model to reduce energy consumption while maintaining occupant comfort. Contrasting with existing approaches, the occupancy model requires no manual training and adapts to changes in occupancy patterns during operation. A prediction-weighted cost function provides conditioning of thermal zones before occupancy begins and reduces system output before occupancy ends. Simulation results with real-world occupancy data demonstrate the algorithm's effectiveness.

show abstract

“…The model used for this study has 41 states: one for zone air and the rest for building structure 3 . It assumes well-mixed air and uses time-invariant convection coefficients.…”

Section: Building Thermal Modelmentioning

confidence: 99%

mentioning

confidence: 99%