PVM-based intelligent predictive control of HVAC systems

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• 作者：A. Ruano^* ; ^{aruano@ualg.pt" class="auth_mail" title="E-mail the corresponding author} ; S. Pesteh^** ; ^{spesteh@csi.fct.ualg.pt" class="auth_mail" title="E-mail the corresponding author} ; S. Silva^*** ; ^{sergiosilva@easysensing.pt" class="auth_mail" title="E-mail the corresponding author} ; H. Duarte^** ; ^{hsduarte@ualg.pt" class="auth_mail" title="E-mail the corresponding author} ; G. Mestre^*** ; ^{goncalomestre@easysensing.pt" class="auth_mail" title="E-mail the corresponding author} ; P.M. Ferreira^**** ; ^{pmf@ciencias.ulisboa.pt" class="auth_mail" title="E-mail the corresponding author} ; H. Khosravani^** ; ^{hkhosravani@csi.fct.ualg.pt" class="auth_mail" title="E-mail the corresponding author} ; R. Horta^**** ; ^{ricardohorta@rolear.pt" class="auth_mail" title="E-mail the corresponding author}
• 关键词：HVAC Model-Based Predictive Control ; Predicted Mean Vote ; Neural Networks ; Multi-Objective Genetic Algorithm ; Weather Station ; Wireless Sensor Networks
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：5
• 页码：371-376
• 全文大小：684 K

文摘

This paper describes the application of a complete MBPC solution for existing HVAC systems, with a focus on the implementation of the objective function employed. Real-time results obtained with this solution, in terms of economical savings and thermal comfort, are compared with standard, temperature regulated control.^*