基于遗传算法的联合循环机组建模和参数辨识

GAO Lin; XIA Junrong; DAI Yiping; KAN Weimin

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基于遗传算法的联合循环机组建模和参数辨识

更新时间：2025-08-13

- 基于遗传算法的联合循环机组建模和参数辨识
- Automation of Electric Power Systems Vol. 34, Issue 4, Pages: 34-37(2010)
- 作者机构：
  
  1. 西安交通大学叶轮机械研究所,陕西省,西安市,710049
  2. 广东电网公司电力科学研究院,广东省,广州市,510000
- 作者简介：
- 基金信息：
- DOI：
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- Published：2010
- 稿件说明：
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GAO Lin, XIA Junrong, DAI Yiping, et al. [J]. Automation of electric power systems, 2010, 34(4): 34-37.
DOI：

GAO Lin, XIA Junrong, DAI Yiping, et al. [J]. Automation of electric power systems, 2010, 34(4): 34-37. DOI：

摘要

随着联合循环机组的不断增加，其对电力系统稳定性的影响也逐步得到重视，建立符合联合循环机组复杂非线性特性并易于通过参数测试获得的数学模型具有重要的现实意义。文中从模型参数辨识的角度出发，在经典联合循环机组非线性模型的基础上，提出了适用于参数测试和辨识的联合循环机组数学模型结构，针对参数辨识的特点提出了基于遗传算法的改进参数辨识算法，并将其应用于某400 MW联合循环机组的参数测试建模。基于遗传算法参数辨识所建立的联合循环机组数学模型的仿真结果与实测信号相一致，证明了所提出的模型和建模方法的可行性与有效性。

Abstract

With the steady increase of combined cycle units， their influence on the electric power system stability is being given increasingly great attention. It is of important practical significance to develop a mathematical model in conformity with their complicated nonlinear characteristics and easily accessible through the test of the parameters. Based on the classical nonlinear model of combined cycle units， this paper presents a new nonlinear model for testing and identifying the combined cycle units. The improved parameter identifying method is proposed based on the genetic algorithm and applied to a 400 MW combined cycle unit. The feasibility and effectiveness of the model and the method proposed are proved.

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