基于改进ARX模型的房间冷负荷预测

控制工程 ›› 2019, Vol. 26 ›› Issue (12): 2258-2263.

基于改进ARX模型的房间冷负荷预测

出版日期:2019-12-20 发布日期:2023-11-29

Prediction of Room Cooling Load Based on Improved ARX Model

Online:2019-12-20 Published:2023-11-29

摘要/Abstract

摘要： 实时冷负荷的精确预测是优化空调系统运行的关键。针对传统的基于室外气象参数和历史冷负荷的ARX模型低普适性的问题，从变量区间划分出发，提出了带温度索引的ARX模型和基于最小二乘支持向量机(LSSVM)的ARX模型。仿真实验结果表明，提出两个模型相比于传统ARX模型，精度均有大幅提升。基于LSSVM的ARX模型具有最高的预测精度和普适性。

关键词:

"> 房间冷负荷；ARX；温度索引；LSSVM；建筑节能

Abstract: Accurate prediction of real-time cooling load is the fundamental work for optimizing the operation of air conditioning systems. Inspired by interval partitioning of variables, two improvements of ARX model are proposed, which are based on temperature index and least squares support vector machine (LSSVM), to solve the problem that traditional ARX model based on outdoor weather parameters and historical cooling load has low universality. Compared with the traditional ARX model, simulation results show that accuracies of the two proposed models are both greatly improved. The ARX model based on LSSVM has the highest prediction accuracy and universality.

Key words: Room cooling load, ARX, temperature index, LSSVM, building energy conservation

邰敏, 李占培, 刘廷章, 金碧瑶, 薛凡.

基于改进ARX模型的房间冷负荷预测 [J]. 控制工程, 2019, 26(12): 2258-2263.

TAI Min, LI Zhan-pei, LIU Ting-zhang, JIN Bi-yao, XUE Fan.

Prediction of Room Cooling Load Based on Improved ARX Model [J]. Control Engineering of China, 2019, 26(12): 2258-2263.