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Grey-box model and identification procedure for domestic thermal storage vessels

机译:家用蓄热容器灰箱模型及辨识程序

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摘要

This paper proposes a model and estimation algorithm, which can automatically characterize a broad range of domestic hot water cylinders and hot water storage buffers. A grey-box compartmental model takes into account the heat loss, internal heat exchange, convection and mixing dynamics associated with water storage systems. Models for these systems are often used in model-predictive controllers. The estimation algorithm is able to identify, in a robust way, the model characteristics for a diversity of storage vessels. It is based on the Markov-Chain Monte-Carlo method, which makes the procedure suited for automation since local minima in the cost function can easily be circumvented. The identification procedure is tested on four different vessels in a distributed thermal storage lab-setup. Two domestic hot water cylinders and two hot water storage buffers have been monitored in a series of charge-discharge tests. It is able to adequately reconstruct the temperature variations inside the storage vessels (errors are smaller than about 5℃). This algorithm is suited for predicting the state-of-charge of thermal energy storage vessels in model based control applications.
机译:本文提出了一种模型和估计算法,可以自动表征各种家用热水瓶和热水存储缓冲器。灰箱隔室模型考虑了与储水系统相关的热损失,内部热交换,对流和混合动力学。这些系统的模型通常用于模型预测控制器中。估计算法能够以鲁棒的方式识别各种存储容器的模型特征。它基于Markov-Chain蒙特卡洛方法,该方法适合自动化,因为可以轻松地规避成本函数中的局部最小值。在分布式储热实验室中,在四个不同的容器上测试了识别过程。在一系列的充放电测试中,对两个家用热水缸和两个热水储存缓冲器进行了监控。它能够适当地重建存储容器内部的温度变化(误差小于5℃)。该算法适用于在基于模型的控制应用中预测热能储存容器的荷电状态。

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