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Determination of the Optimal Order of Grey-Box Models for Short-Time Prediction of Buildings’ Thermal Behavior

机译：短期预测建筑物热行为的灰箱模型的最优阶确定

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The use of grey-box models for short-time forecasting of buildings’ thermal behavior requires the determination of the models’ order since this order could influence the grey-box models’ performance. This paper presents an analysis of the optimal order of these models for different thermal conditions. The novelty of this work consists of considering the influence of the heating conditions on the determination of the performances of grey-box models. The analysis is based on experimental tests that were conducted in a room with different thermal conditions, related to the variation of the heating power. Experimental results were used for the determination of the optimal grey-box models’ order that minimizes the gap between the experimental results and the grey-box forecasting. Results show that the optimal grey-box models’ order depends on the buildings’ thermal conditions, but generally lies between two and three with an error less than 0.2 °C and a fit percent greater than 90%.
机译：使用灰箱模型对建筑物的热行为进行短期预测需要确定模型的顺序，因为此顺序可能会影响灰箱模型的性能。本文介绍了针对不同热条件的这些模型的最佳顺序的分析。这项工作的新颖性在于考虑加热条件对灰箱模型性能确定的影响。该分析基于在具有不同热条件的房间内进行的实验测试，这些实验与加热功率的变化有关。实验结果用于确定最佳灰盒模型的顺序，以最大程度地减少实验结果与灰盒预测之间的差距。结果表明，最佳灰盒模型的顺序取决于建筑物的热工条件，但通常介于2到3之间，误差小于0.2°C，拟合百分比大于90％。

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