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Predictive Control of Multizone HVAC Systems in Non-residential Buildings

机译:非住宅建筑中多态HVAC系统的预测控制

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In France, buildings account for a large part of the energy consumption and carbon emissions. Both are mainly due to Heating, Ventilation and Air-Conditioning (HVAC) systems. So, the present work deals with the predictive control of multizone HVAC systems in non-residential buildings. We used the PMV (Predicted Mean Vote) index as a thermal comfort indicator and developed low-order ANN-based models to be used as controller's internal models. A genetic algorithm allowed the optimization problem to be solved. The proposed strategy allows the operation time of each HVAC sub-system to be optimized (and, as a result, electrical power consumption) and thermal comfort requirements to be met. In order to test this approach, a real non-residential building located in Perpignan (south of France) has been modelled using the EnergyPlus software. The results we obtained in simulation allow the pertinence of the predicitive strategy to be highlighted.
机译:在法国,建筑物占能量消耗和碳排放的很大一部分。两者主要是由于加热,通风和空调(HVAC)系统。因此,本工作涉及在非住宅建筑中对多态HVAC系统的预测控制。我们使用PMV(预测的平均投票)指数作为热舒适度指示器,并开发出低位的基于ANN的模型,以用作控制器的内部模型。遗传算法允许解决优化问题。所提出的策略允许每个HVAC子系统的操作时间优化(以及结果,是电力消耗)和要满足的热舒适要求。为了测试这种方法,位于法国佩皮尼昂(法国南部)的真正的非住宅建筑使用了EnergyPlus软件进行了建模。我们在仿真中获得的结果允许突出显示的预测策略。

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