Forecasting operation of a chiller plant facility using data-driven models

IF 3.5 2区 工程技术 Q1 ENGINEERING, MECHANICAL
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引用次数: 0

Abstract

In recent years, data-driven models have enabled accurate prediction of chiller power consumption and chiller coefficient of performance (COP). This study evaluates the usage of time series Extreme Gradient Boosting (XGBoost) models to predict chiller power consumption and chiller COP of a water-cooled chiller plant. The 10-second measured data used in this study are from the Intelligent Building Agents Laboratory (IBAL), which includes two water-cooled chillers. Preprocessing, data selection, noise analysis, and data smoothing methods influence the accuracy of these data-driven predictions. The data intervals were changed to 30 s, 60 s, and 180 s using down-sampling and averaging strategies to investigate the impact of data preprocessing methods and data resolutions on the accuracy of chiller COP and power consumption models. To overcome the effect of noise on the accuracy of the models of chiller power consumption and COP, two data smoothing methods, the moving average window strategy and the Savitzky-Golay (SG) filter, are applied. The results show that both methods improve the predictions compared to the baseline, with the SG filter slightly outperforming the moving average. Particularly, the mean absolute percentage error of the chiller COP and power consumption models improved from 4.8 to 4.9 for the baseline to 1.9 and 2.3 with the SG filter, respectively. Overall, this study provides a practical guide to developing XGBoost data-driven chiller power consumption and COP prediction models.

利用数据驱动模型预测冷水机组设施的运行情况
近年来,数据驱动模型能够准确预测冷水机组的功耗和冷水机组的性能系数(COP)。本研究评估了使用时间序列极端梯度提升(XGBoost)模型预测水冷式冷水机组的冷水机功耗和冷水机性能系数的情况。本研究使用的 10 秒测量数据来自智能建筑代理实验室(IBAL),其中包括两台水冷式冷水机组。预处理、数据选择、噪声分析和数据平滑方法会影响这些数据驱动预测的准确性。使用向下采样和平均策略将数据间隔改为 30 秒、60 秒和 180 秒,以研究数据预处理方法和数据分辨率对冷风机 COP 和功耗模型准确性的影响。为了克服噪声对冷风机功率消耗和 COP 模型准确性的影响,应用了两种数据平滑方法,即移动平均窗口策略和萨维茨基-戈莱(SG)滤波器。结果表明,与基线相比,这两种方法都提高了预测结果,其中 SG 滤波器略优于移动平均法。特别是,冷风机 COP 和功耗模型的平均绝对百分比误差分别从基线的 4.8 和 4.9 降至 SG 滤波器的 1.9 和 2.3。总之,本研究为开发 XGBoost 数据驱动的冷风机功率消耗和 COP 预测模型提供了实用指南。
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来源期刊
CiteScore
7.30
自引率
12.80%
发文量
363
审稿时长
3.7 months
期刊介绍: The International Journal of Refrigeration is published for the International Institute of Refrigeration (IIR) by Elsevier. It is essential reading for all those wishing to keep abreast of research and industrial news in refrigeration, air conditioning and associated fields. This is particularly important in these times of rapid introduction of alternative refrigerants and the emergence of new technology. The journal has published special issues on alternative refrigerants and novel topics in the field of boiling, condensation, heat pumps, food refrigeration, carbon dioxide, ammonia, hydrocarbons, magnetic refrigeration at room temperature, sorptive cooling, phase change materials and slurries, ejector technology, compressors, and solar cooling. As well as original research papers the International Journal of Refrigeration also includes review articles, papers presented at IIR conferences, short reports and letters describing preliminary results and experimental details, and letters to the Editor on recent areas of discussion and controversy. Other features include forthcoming events, conference reports and book reviews. Papers are published in either English or French with the IIR news section in both languages.
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