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Model predictive control of a thermally activated building system to improve energy management of an experimental building: Part Ⅰ-Modeling and measurements

机译：热激活建筑系统的模型预测控制，以改善实验建筑的能源管理：第一部分：建模和测量

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摘要

A simple way to reduce energy consumption is to minimize heating use during unoccupied periods. This implies the possibility of adjusting the room temperature setpoint. However, systems with a large thermal capacity cannot follow sudden setpoint changes because of their thermal inertia. A model predictive control (MPC) allows the harnessing of this inertia in order to reduce heating costs and improve comfort. This advanced control technique is based on disturbances anticipation (occupation, weather conditions) and requires a model of the system which has to be controlled. Therefore, the use of such controller needs a reliable model that describes well the dynamics of the room on upcoming days. This paper presents a method for the selection of the model (type, level of complexity) to be implemented in a MPC controller to anticipate the control of a long time response floor heating system on a real building. The demonstration room and embedded systems serving as experimental support are presented. Short measurement periods are carried out to identify the model parameter values minimizing the gap between model output and measurement. Gray-box models based on electrical analogy and state-space representation are proposed. They are constructed from physical knowledge and then identified by choosing the most appropriate measurement series. A sensitivity analysis method (Morris) is used to improve the quality of the identified model which satisfies control criteria with two specific validation measurement series. In a complementary paper, the predictive controller integrating the selected model is compared to more conventional management strategies in simulation and on-site with the experimental building. (C) 2018 Elsevier B.V. All rights reserved.
机译：减少能耗的一种简单方法是在闲置期间将供热量降至最低。这暗示了调节室温设定点的可能性。但是，具有大热容量的系统由于其热惯性而无法跟随突然的设定值变化。模型预测控制（MPC）可以利用这种惯性来降低加热成本并提高舒适度。这种先进的控制技术基于对干扰的预测（职业，天气状况），并且需要必须控制的系统模型。因此，使用这种控制器需要一个可靠的模型，该模型可以很好地描述未来几天的房间动态。本文介绍了一种选择模型的方法（类型，复杂程度），该模型将在MPC控制器中实现，以预测对实际建筑物中长时间响应的地板采暖系统的控制。介绍了演示室和嵌入式系统作为实验支持。进行短时间的测量以识别模型参数值，以最小化模型输出和测量之间的差距。提出了基于电气类比和状态空间表示的灰箱模型。它们是从物理知识中构造出来的，然后通过选择最合适的测量系列进行识别。灵敏度分析方法（Morris）用于提高已识别模型的质量，该模型满足两个特定验证测量系列的控制标准。在补充论文中，将集成所选模型的预测控制器与更常规的管理策略进行仿真比较，并在实验大楼中进行现场比较。 （C）2018 Elsevier B.V.保留所有权利。

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  • 来源
    《Energy and Buildings》 |2018年第8期|94-103|共10页
  • 作者

    Viot H.; Sempey A.; Mora L.; Batsale J. C.; Malvestio J.;

  • 作者单位

    Univ Bordeaux, Arts & Metiers ParisTech, Esplanade Arts & Metiers, CNRS,I2M,UMR 5295, F-33400 Talence, France;

    Univ Bordeaux, Arts & Metiers ParisTech, Esplanade Arts & Metiers, CNRS,I2M,UMR 5295, F-33400 Talence, France;

    Univ Bordeaux, Arts & Metiers ParisTech, Esplanade Arts & Metiers, CNRS,I2M,UMR 5295, F-33400 Talence, France;

    Univ Bordeaux, Arts & Metiers ParisTech, Esplanade Arts & Metiers, CNRS,I2M,UMR 5295, F-33400 Talence, France;

    Univ Bordeaux, Arts & Metiers ParisTech, Esplanade Arts & Metiers, CNRS,I2M,UMR 5295, F-33400 Talence, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Low order model; Building parameter identification; Instrumentation; Model predictive control;

    机译：低阶模型;建筑参数识别;仪器仪表;模型预测控制;

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