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Title:
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HOLISTIC OPTIMIZATION OF HVAC SYSTEMS VIA DISTRIBUTED DATA-DRIVEN CONTROL |
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Author(s):
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Karel Macek, Dimitrios Rovas, Mischa Schmidt, Cesar Cesar Valmaseda |
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ISBN:
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978-989-8704-10-8 |
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Editors:
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Ajith P. Abraham, Antonio Palma dos Reis and Jörg Roth |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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HVAC systems, distributed control, data-driven control, lazy learning, dynamic programming. |
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Type:
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Full Paper |
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First Page:
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75 |
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Last Page:
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82 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In the present paper, the control design of Heating, Ventilation and Air Conditioning (HVAC) systems is investigated. In large-scale buildings e.g. hotels or hospitals the high dimension of the control design problem precludes a solution with reasonable computational effort. In this paper, a distributed control strategy is proposed, where interacting agents are operating sub-systems; interaction between these agents can ensure that an optimum solution can be obtained. A novel method to distributed control tis introduced based on data-driven modeling where the strategy is not based on explicit optimization, but on weighted learning of the control rules; two examples of the addressed system are formulated. A significant advantage of the proposed approach consists in minimal assumptions on the addressed system and the most significant disadvantage is the need of sufficiently rich data-sets. |
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