一种太阳能集热系统集热量实时预测的混合建模方法  

A Hybrid Modeling Method for Real-time Prediction of Heat Collection in Solar Heat Collection Systems

作　　者：刘慧 丁绪东 杨东润 张迎 刘忠晨 孙梅 LIU Hui;DING Xu-dong;YANG Dong-run;ZHANG Ying;LIU Zhong-chen;SUN Mei(Shandong Key Laboratory of Intelligent Buildings Technology,School of Information and Electrical Engineering,Shandong Jianzhu University,Jinan 250101,China)

机构地区：[1]山东建筑大学信息与电气工程学院山东省智能建筑技术重点实验室,山东济南250101

出　　处：《计算机与现代化》2022年第10期55-61,共7页Computer and Modernization

基　　金：山东省重大科技创新工程项目(2019JZZY020812);山东省自然科学基金面上项目(ZR2020MF070)。

摘　　要：太阳能集热器的集热量受光照度、环境温度、风速等多种因素的影响,其预测模型很难从预测精度和实时性上同时满足用户需求。本文提出一种实时预测太阳能集热系统集热量的混合建模方法。该方法首先从能量守恒出发,根据热管式太阳能集热系统传热机理推导出集热量的理论模型,并把理论模型中的散热系数、透射率、吸收率等经验参数以及采光面积、散热面积等几何参数集总为模型的未知参数,进而提出混合模型的结构。然后,利用TRNSYS仿真软件搭建太阳能集热器模拟仿真系统,对仿真系统不同的运行工况进行仿真实验,获取用于辨识混合模型未知参数的稳态数据。最后,选用粒子群优化算法(PSO)作为模型参数的辨识方法,利用所获得的稳态数据辨识模型的未知参数。模型预测值与仿真实验结果的比较表明,预测模型简单而精确,能够在各种工况下实时地、高精度地预测太阳能集热器的集热量,其平均相对误差可达到2.02%。该模型在太阳能热泵、太阳能热水器等系统的优化控制领域得以广泛应用。The heat collection of the solar collector is influenced by various factors,such as light intensity,ambient temperature,wind speed and so on,so its prediction model is difficult to meet the user needs both in terms of the prediction accuracy and the real-time performance.A hybrid modeling method to predict the real-time heat collection of solar collector systems is proposed in this paper.The method first starts from energy conservation to derive the theoretical model of the solar collection system according to its heat transfer mechanism,and the empirical parameters,such as the heat dissipation coefficient,the transmissivity,the absorptivity,etc.and the geometric parameters,such as the lighting area,the cooling area,etc.are lumped as the unknown parameters of the model,then the structure of the hybrid model is presented.The TRNSYS simulation software is employed to build a solar collector simulation system,and the simulation experiments on the different operating conditions were performed on the simulation system so as to obtain the steady-state data to identify the unknown parameters of the hybrid model.Finally,the particle optimization algorithm(PSO)is selected as the model parameters identification method to identify the unknown parameters of the model using the obtained steady-state data.The results compared with the model predicted values and the simulation experimental data show that the model is simple and accurate,and can predict the real-time heat collection of solar collector systems with a mean relative error of 2.02%in various working conditions.The model will be widely used in the optimal control of solar heat pumps,solar water heaters and other systems.

关 键 词：太阳能集热系统 混合建模 PSO 参数辨识 太阳能 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]