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System identification of thermal building models for demand response - A practical approach

机译:需求响应热建筑模型的系统识别 - 一种实用的方法

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Model predictive control is a promising control scheme to utilize space heating in buildings for price-based demand response. It is, however, crucial to have an adequate thermal model of the building in order to make this work. It is often very time-consuming to construct these models and common system identification approaches suggest experimental input signals that are difficult to obtain in practice, which often leads to thermal discomfort. This paper proposes an alternative approach where an initial model is identified from historical data and then later re-identified based on control input generated from a model predictive control using the initial model.
机译:模型预测控制是一种有前途的控制方案,用于利用建筑物的空间加热,以获得基于价格的需求响应。然而,对于建筑物的足够热模型来说是至关重要的,以便制定这项工作。构建这些模型和常见的系统识别方法往往是非常耗时的,建议在实践中难以获得的实验输入信号,这通常导致热不适。本文提出了一种替代方法,其中从历史数据识别初始模型,然后基于使用初始模型的模型预测控制生成的控制输入重新识别。

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