|本期目录/Table of Contents|

[1]刘晓莎.基于智能算法的二次再热机组再热汽温控制策略优化[J].工业仪表与自动化装置,2023,(06):3-10+48.[doi:DOI:10.19950/j.cnki.cn61-1121/th.2023.06.001]
　LIU Xiaosha.Optimization of reheat steam temperature control strategy for secondary reheat unit based on intelligent algorithm[J].Industrial Instrumentation & Automation,2023,(06):3-10+48.[doi:DOI:10.19950/j.cnki.cn61-1121/th.2023.06.001]
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基于智能算法的二次再热机组再热汽温控制策略优化

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2023年06期
页码:
3-10+48
栏目:
出版日期:
2023-12-15

文章信息/Info

Title:
Optimization of reheat steam temperature control strategy for secondary reheat unit based on intelligent algorithm
文章编号:
1000-0682（2023）06-0003-08
作者:
刘晓莎
陕西工业职业技术学院，陕西 咸阳 712000
Author(s):
LIU Xiaosha
Shaanxi Polytechnic Institute, Shaanxi Xianyang 712000, China
关键词:
汽温控制; PID; 优化
Keywords:
steam temperature control;  PID;  optimize
分类号:
TM621
DOI:
DOI:10.19950/j.cnki.cn61-1121/th.2023.06.001
文献标志码:
A
摘要:
为解决二次再热机组在运行过程中出现的再热蒸汽温度连续波动、控制品质不佳的问题，以某电厂扩建工程1000 MW超超临界二次再热机组的再热蒸汽温度特性为研究基础，建立了一次再热蒸汽温度和二次再热蒸汽温度传递函数的模型；在该模型基础上设计搭建了具有补偿式模糊自适应特性的PID控制器，借助改进遗传算法控制器的参数进行优化配置；最后将补偿式模糊自适应PID控制器应用到再热蒸汽温度传递函数模型上，以期望获得良好的控制效果。试验结果表明，模糊控制的引入能够缩短调节时间，抑制系统的超调量，表现出更强的非线性、抗干扰性和鲁棒性，相关经验可供后续同类机组参考。
Abstract:
In order to solve the problems of continuous fluctuation of reheat steam temperature and poor control quality during the operation of the secondary reheat unit, based on the study of the reheat steam temperature characteristics of the 1000 MW ultra-supercritical secondary reheat unit of a power plant expansion project, the transfer function models of the primary reheat steam temperature and the secondary reheat steam temperature are established; Based on the model, a PID controller with compensated fuzzy adaptive characteristics is designed and built, and the parameters of the improved genetic algorithm controller are optimized; Finally, the compensated fuzzy adaptive PID controller is applied to the transfer function model of reheat steam temperature in order to obtain good control effect. The test results show that the introduction of fuzzy control can shorten the regulating time, restrain the overshoot of the system, and show stronger nonlinearity, anti-interference and robustness. The relevant experience can be used as a reference for similar units in the future.

参考文献/References:

[1] 殷亚宁.二次再热超超临界机组应用现状及发展[J].电站系统工程,2013(2):37-38.

[2] 施爱阳,陈云芬,邵爱华.二次再热超超临界机组的设计探讨[J].锅炉制造,2014(2):5-6.
[3] 余炎,刘晓澜,范世望.二次再热汽轮机关键技术分析及探讨[J].热力透平,2013,42(2):69-72.
[4] KAJER S. A modified double reheat cycle[C]// Proceedings of the ASME 2010 Power Conference, Chicago, 2010.
[5] 张巍,卢宇清.基于在线自适应遗传算法的PID参数整定和优化[J].计算机仿真,2011(12):154-157.
[6] 方彦军,易凤飞,胡文凯.基于遗传算法的广义预测PID控制及其在锅炉主汽温系统中的应用[J].武汉大学学报(工学版),2013(3):386-392.
[7] 韩轶楠,王立德.遗传优化的模糊-PID控制在柴油机转速控制中的应用[J].电气应用,2013(16):26-29.
[8] 郭亦文,李军,耿林霄.基于遗传算法获取模糊规则[J].计算机应用,2014(10):2899-2903.
[9] BRANKE J,KAUBLER T,SMIDT C,et al.A multi- population approach to dynamic optimization problems[M] //PARMEE IODN C. Evolutionary Design and Manufacture. London: Springer-Verlag,2000:299-308.
[10] 周东阳,魏湘,蔡宝玲,等.超超临界1000 MW机组仿真系统开发与应用[J].热力发电,2011(11):76-77.
[11] 李世勇.模糊控制?神经控制和智能控制论[M].哈尔滨:哈尔滨工业大学出版社,1998:22-25.
[12] 张佩.基于改进遗传算法的给水泵汽轮机调节气阀控制[J].工业仪表与自动化装置,2023(1):116-120.
[13] 何彬浩,傅志敏,吴巍,等.基于改进遗传算法与动态规划的输水泵站日优化调度[J].水电能源科学,2023,41(2): 128-132.?/div>
[14] 胡新平,贺玉芝,倪巍伟,等.基于赌轮选择遗传算法的数据隐藏发布方法[J].计算机研究与发展,2012,49(11): 2432-2439.?div>[15] 陈洪华,张立.基于“赌轮选择法”的信息系统属性约简方法研究[J].科技创新与应用,2012(29):6-7.

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备注/Memo

备注/Memo:
收稿日期：2023-03-15?div>
基金项目：
国家科技支撑计划资助项目（2020YFA03B01）?/div>

作者简介：
刘晓莎(1989—)，女，研究生，讲师，主要研究方向为工业大数据与智能发电技术。
更新日期/Last Update: 1900-01-01