基于混合遗传算法的暖通空调热能动力参数识别研究  

Research on Identification of Thermal Power Parameter of HVAC Based on Hybrid Genetic Algorithm

作　　者：王俊 WANG Jun(China Municipal Engineering Northwest Design and Research Institute Co.,Ltd.Shanxi Branch Xi'an 710061,China)

机构地区：[1]中国市政工程西北设计研究院有限公司陕西分公司,陕西西安710061

出　　处：《河南科技》2024年第6期34-37,共4页Henan Science and Technology

摘　　要：【目的】针对现有的暖通空调热能动力参数识别方法存在识别结果R-squared值较小,无法满足识别精度要求的问题,提出了基于混合遗传算法的暖通空调热能动力参数识别研究。【方法】首先对暖通空调热能多自由度动力振动正问题进行精细积分求解。然后利用混合遗传算法,建立反问题目标函数,并完成精英搜索。最后利用流体网络方程,完成暖通空调热能动力参数的辨识。【结果】通过对比实验,证明所提方法得到的结果R-squared值更接近1,说明该方法的暖通空调热能动力参数识别精度更高,方法性能更理想。【结论】该方法能够为暖通空调系统优化、节能减排、故障诊断、智能控制等提供更可靠的基础依据。[Purposes]In response to the problem that existing methods for identifying thermal power parameters in HVAC systems have small R-squared values that cannot meet the recognition accuracy requirements,this paper proposes a study on identifying thermal power parameters in HVAC systems based on a hybrid genetic algorithm.[Methods]Firstly,this paper performs precise integration to solve the multi degree of freedom dynamic vibration forward problem of HVAC thermal energy.Then,a hybrid genetic algorithm is used to establish the inverse problem objective function and complete the elite search.Finally,the identification of thermal power parameters for HVAC is completed using fluid network equations.[Findings]Through comparative experiments,it has been proven that the R-squared value obtained by the proposed method is closer to 1,indicating that the identification accuracy of the HVAC thermal power parameters is higher and the performance of the method is more ideal.[Conclusions]This method can provide a more reliable foundation and basis for optimizing HVAC systems,energy conservation and emission reduction,fault diagnosis,and intelligent control.

关 键 词：混合遗传算法 空调 识别 动力参数 热能 暖通 

分 类 号：TU831[建筑科学—供热、供燃气、通风及空调工程]