文章基本信息

标题：A Bilinear Approach to Model Predictive Control for Thermal Conditioning of Adaptive Buildings
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作者：Marius Oei ; Janine Guenther ; Michael Böhm 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：8383-8388
DOI：10.1016/j.ifacol.2020.12.1593
语种：English
出版社：Elsevier
摘要：AbstractThe high resource and energy consumption of the building sector in both construction and operation is a growing problem worldwide. The largest contributor to operational energy consumption is thermal conditioning of the indoor space. In this context, inefficient control algorithms or parametrizations become a serious problem requiring thermal simulation models of buildings for system sizing and control parameter adjustments. However, the high complexity of the underlying dynamic models makes the design of model-based controllers difficult. Furthermore, typically used control schemes such as PI-control cannot incorporate all types of actuators that an adaptive building may provide.In this work, we derive a bilinear thermal model for adaptive ultra-lightweight buildings from the linearized model output of the Modelica library BuildingSystems by incorporating environmental and internal disturbances as well as a number of possible actuators for an adaptive building into the model as time-varying bilinear inputs.Based on the bilinear model, a model-predictive control algorithm is devised that incorporates disturbance forecasts. Exemplary simulations for a summer day show the efficacy of the control algorithm in employing indirect actuation.
关键词：KeywordsAdaptive buildingsmodel predictive controlbilinear model