Building model identification during regular operation - empirical results and challenges
| Autor: | Qie Hu, Frauke Oldewurtel, Evangelos Vrettos, Datong P. Zhou, Claire J. Tomlin, Maximilian Balandat |
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| Rok vydání: | 2016 |
| Předmět: |
Flexibility (engineering)
Engineering Building science Occupancy business.industry 020209 energy Building model Control engineering Systems and Control (eess.SY) 02 engineering and technology Reliability engineering Identification (information) Air conditioning FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Computer Science - Systems and Control business Building automation Efficient energy use |
| Zdroj: | ACC |
| DOI: | 10.1109/acc.2016.7524980 |
| Popis: | The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal dynamics is required. In this paper, we identify a physics-based model of a multi-purpose commercial building including its heating, ventilation and air conditioning system during regular operation. We present our empirical results and show that large uncertainties in internal heat gains, due to occupancy and equipment, present several challenges in utilizing the building model for long-term prediction. In addition, we show that by learning these uncertain loads online and dynamically updating the building model, prediction accuracy is improved significantly. Comment: The 2016 American Control Conference, July 6-8, Boston, USA |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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