制冷学报Issue(5)：87-93,106,8.DOI:10.3969/j.issn.0253-4339.2015.05.087
基于PSO-SVR的冷水机组运行能效预测模型研究
Research on COP Prediction Model of Chiller Based on PSO-SVR
周璇 1蔡盼盼 1练斯甄 1闫军威1
作者信息
- 1. 华南理工大学机械与汽车工程学院 广州 510640
- 折叠
摘要
Abstract
Since the difficulty of building mechanism model and the structure of COP model of chiller is complex, greatly affected by op-erating parameter, a COP prediction model of chiller is proposed based on Support Vector Regression, and the parameters are optimized by Particle Swarm Optimization algorithm. In this paper, 396 sets of operating data of chiller of a shopping mall are randomly selected to train and test this model. The results shows that the prediction accuracy of SVR model based on PSO optimization algorithm is higher than that of BP neural network and the relative error is within 3%. At last, operating data of two days in summer and transition season are randomly selected to verify the model. The relative error is within 5%. So this model can provide theoretical basis for the chiller energy efficiency a-nalysis, fault detection and diagnosis and optimizing control.关键词
冷水机组/运行能效/预测模型/支持向量回归机/粒子群算法Key words
chiller/COP/prediction model/support vector regression/particle swarm optimization分类
通用工业技术引用本文复制引用
周璇,蔡盼盼,练斯甄,闫军威..基于PSO-SVR的冷水机组运行能效预测模型研究[J].制冷学报,2015,(5):87-93,106,8.
