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Record Nr. |
UNINA9910253982303321 |
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Autore |
Yao Ye |
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Titolo |
Modeling and Control in Air-conditioning Systems / / by Ye Yao, Yuebin Yu |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2017 |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (XXI, 479 p. 272 illus., 46 illus. in color.) |
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Collana |
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Energy and Environment Research in China, , 2197-0238 |
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Disciplina |
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Soggetti |
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Energy consumption |
Building construction |
Mathematical models |
Sustainable development |
Energy Efficiency |
Building Physics, HVAC |
Mathematical Modeling and Industrial Mathematics |
Sustainable Development |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- State-space modelling for air-conditioning system -- Modelling based on graph theory and structure-matrix theory -- Control design based on state-space model -- Air-conditioning load forecasting model -- Optimal operation and energy analysis modelling for air-conditioning system -- Thermal comfort of human body indoors -- Multizone network modelling of building ventilation and contaminant transport -- Computational fluid dynamics of building environment -- Coupled multizone and CFD modelling of building environment -- New trends of advanced modelling of building environment. |
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Sommario/riassunto |
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This book investigates the latest modeling and control technologies in the context of air-conditioning systems. Firstly, it introduces the state-space method for developing dynamic models of all components in a central air-conditioning system. The models are primarily nonlinear and based on the fundamental principle of energy and mass |
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conservation, and are transformed into state-space form through linearization. The book goes on to describe and discuss the state-space models with the help of graph theory and the structure-matrix theory. Subsequently, virtual sensor calibration and virtual sensing methods (which are very useful for real system control) are illustrated together with a case study. Model-based predictive control and state-space feedback control are applied to air-conditioning systems to yield better local control, while the air-side synergic control scheme and a global optimization strategy based on the decomposition-coordination method are developed so as to achieve energy conservation in the central air-conditioning system. Lastly, control strategies for VAV systems including total air volume control and trim & response static pressure control are investigated in practice. . |
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