Research on prediction model of heat consumption rate of steam turbine based on FOA-LSSVM

WANG Huijie; FAN Zhiyuan; XU Xiaogang

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Research on prediction model of heat consumption rate of steam turbine based on FOA-LSSVM

Thermal Power Generation Issue 4, (2017)

更新时间：2025-09-28

- Research on prediction model of heat consumption rate of steam turbine based on FOA-LSSVM
- 作者机构：
  
  华北电力大学能源动力与机械工程学院,河北,保定,071003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM621.4
- Published Online：26 April 2017，
  
  Published：2017
- 稿件说明：
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WANG Huijie, FAN Zhiyuan, XU Xiaogang. Research on prediction model of heat consumption rate of steam turbine based on FOA-LSSVM[J]. Thermal Power Generation, 2017, (4).
DOI：

WANG Huijie, FAN Zhiyuan, XU Xiaogang. Research on prediction model of heat consumption rate of steam turbine based on FOA-LSSVM[J]. Thermal Power Generation, 2017, (4). DOI：

摘要

为了准确描述可控参数与热耗率之间的关系，采用偏相关分析法，结合汽轮机热耗率方程确定了影响汽轮机热耗率的5个主要变量，并将其作为模型的输入参数；通过比较分析，选用RBF_kernel为模型的核函数；利用果蝇优化算法(FOA)对最小二乘支持向量机(LSSVM)的惩罚因子和核径向范围2个参数进行优化，建立了FOA-LSSVM黑箱模型；以FOA-LSSVM为基础，建立了预测汽轮机热耗率的数学模型，并将其与采用LSSVM、RBF神经网络建立的热耗率预测模型进行对比，同时分析了该模型的鲁棒性。结果表明，基于FOA-LSSVM的汽轮机热耗率预测模型具有精度高、泛化能力强、鲁棒性强的优点。该模型为机组热经济性诊断、参数寻优提供了理论依据，具有一定的工程应用价值。

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