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Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings

机译：非住宅建筑中多区域供暖，通风和空调系统的预测控制

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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. Because older, oversized or poorly maintained systems may be using more energy and costing more to operate than necessary, new management approaches are needed. In addition, energy efficiency can be improved in central heating and cooling systems by introducing zoned operation. So, the present work deals with the predictive control of multizone HVAC systems in non-residential buildings. First, a real non-residential building located in Perpignan (south of France) has been modelled using the EnergyPlus software. We used the predicted mean vote (PMV) 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. In order to appraise the proposed management strategy, it has been compared to basic scheduling techniques. Using the proposed strategy, the operation of all the HVAC subsystems is optimized by computing the right time to turn them on and off, in both heating and cooling modes. Energy consumption is minimized and thermal comfort requirements are met. So, the simulation results highlight the pertinence of a predicitive approach for multizone HVAC systems management. (C) 2015 Elsevier B.V. All rights reserved.
机译：在法国，建筑物占能源消耗和碳排放的很大一部分。两者均主要归因于供暖，通风和空调（HVAC）系统。由于较旧的，超大型的或维护不善的系统可能会比必要的方式消耗更多的能源和更多的运行成本，因此需要新的管理方法。此外，通过引入分区操作，可以提高中央供暖和制冷系统的能源效率。因此，本工作涉及非住宅建筑中多区域HVAC系统的预测控制。首先，已经使用EnergyPlus软件对位于佩皮尼昂（法国南部）的一栋真正的非住宅建筑进行了建模。我们使用预测的平均投票（PMV）指数作为热舒适度指标，并开发了基于ANN的低阶模型作为控制器的内部模型。遗传算法可以解决优化问题。为了评估提议的管理策略，已将其与基本调度技术进行了比较。使用提出的策略，通过计算在加热和冷却模式下打开和关闭它们的正确时间，可以优化所有HVAC子系统的运行。能耗降至最低，并满足热舒适性要求。因此，仿真结果突出了针对多区域HVAC系统管理的预测方法的相关性。 （C）2015 Elsevier B.V.保留所有权利。

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