大型风力发电机输出功率建模方法

兰州理工大学学报 ›› 2023, Vol. 49 ›› Issue (4): 49-53.

大型风力发电机输出功率建模方法

张岩^*1, 马壮², 董博², 郑玉巧²

1.甘肃省特种设备检验检测研究院, 甘肃兰州 730050;
2.兰州理工大学机电工程学院, 甘肃兰州 730050

收稿日期:2022-07-24 出版日期:2023-08-28 发布日期:2023-08-29
通讯作者: 张岩(1982-),男,甘肃兰州人,高级工程师. Email:79144469@qq.com
基金资助:
国家自然科学基金(51965034)

Research on output power modeling method of large wind turbine

ZHANG Yan¹, MA Zhuang², DONG Bo², ZHENG Yu-qiao²

1. Gansu Province Special Equipment Inspection and Testing Institute, Lanzhou 730050, China;
2. School of Mechanical and Electrical Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China

Received:2022-07-24 Online:2023-08-28 Published:2023-08-29

摘要/Abstract

摘要： 输入风速的变化特点直接影响着风力发电机输出功率建模.采用非线性最小二乘法和差分进化算法计算参数,结合具备较高精度的启发式算法寻优构建,运用Logistic函数进行大型风力发电机输出功率建模研究,并对比分析不同方法对应风力发电机输出功率模型的建模精度.结果表明:非线性最小二乘法更适合所提模型参数计算,传统输出功率模型高精度源于模型中人为定义的额定功率值,Logistic函数输出功率模型无需人为定义额定功率值,在相同条件下该输出功率特性模型建模精度较优.

关键词: 风力发电机, 功率特性模型, Logistic函数

Abstract: The variation characteristics of input wind speed directly affect the output power modeling of wind turbine. In this paper, nonlinear least square method and differential evolution algorithm are used to calculate parameters, and Logistic function is used to model the output power of wind turbine, combined with the high accuracy of heuristic algorithms in finding the optimal construction. Then, the modeling accuracy of the three methods for output power model is compared. The results show that the nonlinear least squares method is more suitable for the calculation of the proposed model parameters. The high accuracy of the traditional output power model is derived from the artificially defined rated power value in the model, while the Logistic function output power model does not need to artificially define the rated power value, the modeling accuracy of which is better under the same conditions.

Key words: wind turbine, power characteristic model, Logistic function

中图分类号:

TK83

张岩, 马壮, 董博, 郑玉巧. 大型风力发电机输出功率建模方法[J]. 兰州理工大学学报, 2023, 49(4): 49-53.

ZHANG Yan, MA Zhuang, DONG Bo, ZHENG Yu-qiao. Research on output power modeling method of large wind turbine[J]. Journal of Lanzhou University of Technology, 2023, 49(4): 49-53.

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