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Robustness of a regression approach, aimed for calibration of whole building energy simulation tools

机译:回归方法的鲁棒性,旨在校准整个建筑能耗模拟工具

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摘要

An approach, able to easily and effectively integrate field measured data in whole building energy simulation (BES) models is crucial to increase simulation accuracy for existing buildings. In this paper, the robustness of a linear regression method for extracting transmission losses above ground (including air leakage) and ground heat loss parameters are analyzed. The regression method is evaluated on two documented and monitored multifamily buildings with mechanical supply and exhaust ventilation systems, with and without heat recovery. The obtained results are found to be robust, with variations less than 2% in the extracted estimates of transmission losses above ground (including air leakage) and with a high goodness of fit (R~2 >0.96) against measured data from two years. In addition, the estimations of the buildings ground heat loss were in good agreement with calculations in accordance with EN ISO 13370:2007. The high quality output from the used regression method serves as good prerequisites for the method to be used in conjunction with BES models to aid the analyst in a BES calibration process.
机译:一种能够轻松有效地将实地测量数据集成到整个建筑能源模拟(BES)模型中的方法,对于提高现有建筑的模拟精度至关重要。在本文中,分析了用于提取地面以上传输损耗(包括空气泄漏)和地面热损耗参数的线性回归方法的鲁棒性。该回归方法是在两套有文件记录和监控的,具有机械供气和排风系统,有热回收和无热回收的多户住宅中进行评估的。结果表明,所获得的结果是可靠的,相对于两年来的实测数据,提取的地面传输损失(包括漏气)的估计变化小于2%,并且拟合度很高(R〜2> 0.96)。此外,建筑物地热损失的估算与根据EN ISO 13370:2007进行的计算非常吻合。所用回归方法的高质量输出是与BES模型结合使用以帮助分析人员进行BES校准过程的良好前提。

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