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Wind farm active power dispatching algorithm based on Grey Incidence

2023-06-08

【论文推荐】西安工业大学王坤等：基于灰色关联度的风电场有功功率分配算法

摘要

本文提出了一种基于灰色关联度的风电场有功功率分配算法，该算法不依赖于精确的风机数学模型。根据风力机在不同风速下的启停数据，采用灰色关联度得到变速系统和变桨距系统对功率调节的参与程度的权重系数。采用b样条函数对全风速范围下的入射系数曲线进行拟合，得到各风力机的功率调节能力。最后，在MATLAB中对基于各风力机调节能力的WFAPD算法与风速加权电力分配算法进行了比较。仿真结果表明，风电场有功功率波动较小，风机转速更平稳，有效降低了高速风机的疲劳负荷。

Wind farm active power dispatching algorithm based on Grey Incidence

基于灰色关联度的风电场有功功率分配算法

Binbin Zhang¹, Mengxin Jia¹, Chaobo Chen¹, Kun Wang¹, Jichao Li¹

1. School of Electronic and Information Engineering, Xi’an Technological University, Xi’an 710021, P. R. China

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Wind Farm Active Power Dispatching Algorithm Base on Grey Incidence

Abstract

This study proposes a wind farm active power dispatching (WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching (WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of high- speed turbines is effectively reduced.

Keywords

Wind farm; Active power dispatching; Grey incidence; B-spline function.

Fig. 1 Curtailment power control schematic of variable speed and variable pitch wind turbine

Fig. 2 Schematic of GI-WFAPD

Fig. 3 Schematic of GI-WFAPD

Fig. 4 Curves of output power (a), rotating speed (b), and pitch angle (c) of wind turbine at 8 m/s

Fig. 5 Weighting coefficient curve of the variable speed system based on the B-spline function fitting

Fig. 6 Power regulation capacity of the wind turbine at a wind speed of 8.5 m/s

Fig. 7 Wind speed of 10 wind turbines

Fig. 8 Wind farm active power curves of two dispatching algorithms

Fig. 9 Rotor speed of the wind turbines using the WSWPD algorithm

Fig. 10 Rotor speed of the wind turbines using the GI-WFAPD algorithm

Fig. 11 Pitch angle of the wind turbines using the WSWPD algorithm

Fig. 12 Pitch angle of the wind turbines using the GI-WFAPD algorithm

Fig. 13 IAE index of the two dispatching algorithms

Fig. 14 Power smoothness of the two dispatching

Fig. 15 Rotor speed smoothness of the two dispatching algorithms

Fig. 16 Pitch angle balance coefficient of the two dispatching algorithms

本文引文信息

Zhang BB, Jia MX, Chen CB, et al (2023) Wind farm active power dispatching algorithm based on Grey Incidence. Global Energy Interconnection, 6(2): 175-183

张彬彬，贾梦欣，陈超波等 (2023) 基于灰色关联度的风电场有功功率分配算法. 全球能源互联网（英文）, 6(2): 175-183

Biographies

Binbin Zhang

Binbin Zhang received bachelor’s degree at Xi’an Technological University, Xi’an, Shaanxi, 2008; received master degree at Xi’an Technological University, Xi’an, Shaanxi, 2015; received phD degree at Xi’an University of Technology, Xi’an, Shaanxi, 2021. He is currently working in Xi’an Technological University. His research interest covers intelligent control, wind turbine.

Mengxin Jia

Mengxin Jia received bachelor’s degree at North China University of Science and Technology, Tangshan, Hebei, 2017. She is pursuing a master degree at Xi’an Technological University, Xi’an, Shaanxi. Her research interests include wind turbines.

Chaobo Chen

Chaobo Chen received bachelor degree at Xi’an Technological University, Xi’an, Shaanxi, 2001; received master degree at Xi’an Technological University, Xi’an, Shaanxi, 2009; received phD degree at Xi’an University of Technology, Xi’an, Shaanxi, 2022. He is currently working in Xi’an Technological University. His research interest interests include intelligent control, fault diagnosis, and fault tolerant control.

Kun Wang

Kun Wang received bachelor degree at Xi’an Technological University, Xi’an, Shaanxi, 1998; received master degree at Xi’an Jiaotong University, Xi’an, Shaanxi, 2005. She is working in Xi’an Technological University. Her research interests cover control theory and control engineering, pattern recognition, and intelligent systems.

Jichao Li

Jichao Li received bachelor degree at Xi’an Technological University, Xi’an, Shaanxi, 2013; received master degree at Xi’ an Technological University, Xi’an, Shaanxi, 2016. He is working in Xi’an Technological University. His research interests include intelligent control.

编辑：刘通明

审核：王伟

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