基于CEEMDAN和WTCN-GRU的中央空调负荷混合预测模型

IF 3.5 2区 工程技术 Q1 ENGINEERING, MECHANICAL
Yang Guo , Mengyao Chen , Hong Wang , Pan Chu , Yingjie Sheng , Hao Li
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引用次数: 0

摘要

准确的负荷预测是中央空调系统节能优化控制的重要基础,对建筑节能减排至关重要。针对现有负荷预测模型精度低的问题,提出了一种基于自适应噪声的完全集成经验模态分解(CEEMDAN)和改进的时间卷积网络(WTCN) -门控循环单元(GRU)相结合的混合模型的空调负荷预测方法。首先,采用Pearson相关分析,选择高度相关的影响因素作为特征输入。然后应用CEEMDAN对原始数据进行分解和重构,以减轻数据的非平稳性,提高数据质量。其次,对TCN中各残差块的第一层卷积进行改进,增强特征提取能力;第三,利用GRU中的门控机制处理数据中的时间关系,对空调负荷进行预测。最后,利用办公楼中央空调负荷数据进行了实验验证。结果表明,该模型优于其他基准模型,显著提高了建筑空调负荷预测的准确性。在优化建筑能耗控制方面具有广阔的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid forecasting model for central air conditioning load based on CEEMDAN and WTCN-GRU
Accurate load prediction is an important foundation for the energy-saving and optimized control of central air conditioning systems, and it is crucial for energy conservation and emissions reduction in buildings. To address the issues of low accuracy in existing load forecasting models, this paper proposes a load prediction method of air conditioning based on hybrid model combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and an improved Temporal Convolutional Network (WTCN) -Gated Recurrent Unit (GRU). Firstly, Pearson correlation analysis is used to select highly correlated influencing factors as feature inputs. CEEMDAN is then applied to decompose and reconstruct the original data to mitigate data non-stationarity and improve data quality. Secondly, the first-layer convolution of each residual block in the TCN is improved to enhance feature extraction capability. Thirdly, the gating mechanism in the GRU is utilized to handle the temporal relationships in the data and predict the air conditioning load. Finally, experiments are conducted using the central air conditioning load data from office building for validation. The results show that the proposed model outperforms other benchmark models, significantly improving the accuracy of building air conditioning load forecasting. It holds promising application prospects in optimizing building energy consumption control.
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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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