基于VMD-GRU网络大型公共建筑冷负荷预测  

Research on cold load forecasting model of large public buildings based on VMD-GRU network cold load forecasting model of large public buildings based on VMD-GRU network

作　　者：于军琪[1] 解云飞 赵安军[1] 王佳丽[1] 冉彤 惠蕾蕾 YU Junqi;XIE Yunfei;ZHAO Anjun;WANG Jiai;RAN Tong;HUI Leiei(School of Building Services Science and Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,P.R.China)

机构地区：[1]西安建筑科技大学建筑设备科学与工程学院,西安710055

出　　处：《重庆大学学报》2023年第12期66-79,共14页Journal of Chongqing University

基　　金：陕西省重点研发计划资助项目(Z20180244);碑林区应用技术研发资助项目(GX1903)。

摘　　要：基于冷负荷时间序列固有的复杂性和不规则性,针对预测过程中容易出现梯度消失、模态混叠和过拟合等问题,提出一种集成变分模态分解(variational mode decomposition,VMD)和门控循环单元网络(gated recurrent unit,GRU)的VMD-GRU模型。对原始数据进行相关性分析,挑选出相关性高的进行预测;使用VMD将原始数据序列分解为独立固有模式函数;使用GRU对每个分量进行预测;将分量预测结果相加得出冷负荷预测值。为验证模型的有效性,以西安某大型公共建筑为例进行能耗分析,并与BP、GRU、EMD-BP、VMD-BP、EMD-GRU等其他预测模型进行对比。实验结果表明,提出的VMD-GRU模型可有效解决梯度消失、模态混叠和过拟合等问题,预测精度显著提高,预测效果优于其它预测模型,符合大型公共建筑冷负荷的变化规律,为节能优化提供有力数据支撑。Due to the inherent complexity and irregularity of cold load time series data,problems such as gradient disappearance,modal aliasing and over-fitting are prone to occur during the prediction process.Predicting the cold load of large public buildings remains a challenging task.To solve this problem and improve the prediction accuracy,the VMD-GRU model is proposed in this study.Real data from large public buildings were utilized to test the proposed model.The prediction process involves the following steps:1)Correlation analysis of the original data and selection of highly correlated predictors;2)Decomposition of the original data sequence into independent eigenmode functions using VMD;3)Prediction of each component using GRU;4)Aggregation of component prediction results to obtain the cold load prediction value.To validate the model's effectiveness,a large public building in Xi'an is taken as an example for energy consumption analysis.The results are compared with other prediction models,including BP,GRU,EMD-BP,VMD-BP,EMD-GRU.Experimental results show that the proposed model effectively solves the problems,such as gradient disappearance,modal aliasing and over-fitting,accurately predicting the cold load of large public buildings.

关 键 词：大型公共建筑 预测算法 相关性分析 变分模态分解 

分 类 号：TU831[建筑科学—供热、供燃气、通风及空调工程]