Determination of optimal initial steam pressure of turbine based on relevance vector machine

LIU Chao; NIU Peifeng; DUAN Xiaolong; LI Guoqiang; ZHANG Xianchen

doi:10.11949/j.issn.0438-1157.20151407

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Determination of optimal initial steam pressure of turbine based on relevance vector machine

更新时间：2025-12-10

- Determination of optimal initial steam pressure of turbine based on relevance vector machine
- CIESC Journal Issue 9, Pages: 3812-3816(2016)
- 作者机构：
  
  燕山大学工业计算机控制工程河北省重点实验室,河北,秦皇岛,066004
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20151407
  CLC： K323
- Online First：05 September 2016，
  
  Published：05 September 2016
- 稿件说明：
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LIU Chao, NIU Peifeng, DUAN Xiaolong, et al. Determination of optimal initial steam pressure of turbine based on relevance vector machine[J]. CIESC Journal, 2016, (9): 3812-3816.
DOI：

LIU Chao, NIU Peifeng, DUAN Xiaolong, et al. Determination of optimal initial steam pressure of turbine based on relevance vector machine[J]. CIESC Journal, 2016, (9): 3812-3816. DOI： 10.11949/j.issn.0438-1157.20151407.

摘要

为了有效计算最优初压，首先提出一种基于模拟退火和混合迁移的生物地理学优化算法（B-BBO-SA）优化相关向量机（RVM）的热耗率预测模型；然后在该模型的基础上利用B-BBO-SA算法寻找各个负荷下热耗率最小时所对应的主蒸汽压力。通过与B-BBO-SA-SVM进行比较，B-BBO-SA-RVM具有更好的泛化能力；另外，得到的最优初压与设计初压存在着一定的差别，它更能准确地指导汽轮机的安全、经济运行。

Abstract

In order to calculate the optimal initial pressure effectively

a heat rate forecasting model is presented based on the optimized relevance vector machine (RVM)

in which the blended biogeography-based optimization based on the simulated annealing (B-BBO-SA) is adopted to optimize the parameter of RVM. Then

B-BBO-SA is employed to seek the optimal initial pressure under all loads based on the forecasting model. The comparison with B-BBO-SA-SVM show that the B-BBO-SA-RVM has better generalization abilities. In addition

there are some differences between the found optimal initial pressure and the designed one

and the found one can better ensure the turbine run safely and economically.

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