建立离心式冷水机组运行能效模型对其运行能效分析以及优化控制意义重大。离心式冷水机组结构复杂且其运行能效受多种因素的影响，机理建模困难，而支持向量回归机能够较好的解决非线性高维问题，因此提出了基于支持向量回归机的离心式冷水机组运行能效建模方法，提高了模型的精度。同时以某商场离心式冷水机组为例，对该方法进行验证，采用平均相对误差（MRE）和均方根误差（RMSE）对模型精度进行评价。结果表明，基于支持向量回归机的冷水机组模型MRE值较BP神经网络模型提高了37.93%，RMSE值较BP神经网络模型提高了28.81%，能准确的反应离心式冷水机组的运行能效。%Establishment of the COP model of centrifugal chiller is of great significance to it's energy efficiency analysis andoptimal control. Since centrifugal chillers operation energy efficiency structure is complex, which is greatly affected by operating parameters, it is difficult to build the mechanism model. In this paper, a prediction model of centrifugal chillers operation energy efficiency was proposed based on Support Vector Regression, whose model parameters were optimized by Particle Swarm Optimization algorithm. This model was verified by centrifugal chillers equipped in a shopping mall, mean relative error (MRE) and root mean squared erro (RMSE) was adopted as the evaluation of the prediction accuracy. The results showed that the prediction accuracy MRE of SVR model based on PSO optimization algorithm was 37.93 % higher than that of BP neural network, and RMSE was28.81% higher than of BP neural network. This model can provide theorical basisfor the centrifugal chiller energy efficiency analysis, fault detection and diagnosis, and optimizing control.
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