基于旋转门算法的风速和风功率爬坡事件的识别方法及特征分析*

doi:10.7523/j.ucas.2023.014

中国科学院大学学报

基于旋转门算法的风速和风功率爬坡事件的识别方法及特征分析^*

梁志^1,2, 张哲^1,2, 师宇¹, 刘磊^1†

1 中国科学院大气物理研究所,北京 100029;
2 中国科学院大学,北京 100049

收稿日期:2022-11-02 修回日期:2023-02-21 发布日期:2023-03-21
通讯作者: ^†E-mail：liulei@mail.iap.ac.cn
基金资助:
^*国家自然科学基金面上项目 (41675012)资助

Detection method and characterization of Ramp event of wind speed and wind power based on Swinging Door Algorithm

LIANG Zhi^1,2, ZHANG Zhe^1,2, SHI Yu¹, LIU Lei¹

1 Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-11-02 Revised:2023-02-21 Published:2023-03-21

摘要/Abstract

摘要： 风速的爬坡事件是风速在短时间内的大幅度增加或减少,风电场功率同时发生大幅度的改变,会影响到电网安全运行,甚至引发电网局部频率降低和电压崩溃等事故。本文选取了风电场内风机和气象铁塔的同期数据,通过旋转门算法SDA（Swinging Door Algorithm）识别了爬坡事件,分析了爬坡事件的持续时间、爬坡幅度和变化速率,讨论了山地地形对爬坡事件的影响。本文基于旋转门算法设计了风速和功率的爬坡事件的识别算法,算法参数取值为时间阈值4h、风速阈值6m s-1、功率阈值1000kW,算法的识别效果较好,可有效识别爬坡事件。针对不同风机的爬坡事件识别,本文建议采用额定风速与切入风速差值的2/3数值作为风速阈值参数,采用额定功率的2/3数值作为功率阈值参数。山地地形对爬坡事件的影响较为显著,爬坡事件与风机处海拔高度、平均风速较为相关,不同地形下风机的爬坡事件的时间比例分布在6.5%到9.8%范围内,平均值为7.8%。

关键词: 爬坡事件, 识别方法, 旋转门算法, 风电场

Abstract: The ramp event of wind speed is a large increase or decrease in wind speed within a short period, causing a huge change in wind farm power, affecting the safe operation of the grid and even triggering accidents such as frequency reduction and voltage collapse. This paper selects the simultaneous data of wind turbines and meteorological towers in wind farms, identifies the climbing events by the Swinging Door Algorithm (SDA), analyzes the duration, magnitude and change rate of the ramp events, and discusses the influence of mountainous terrain on the climbing events. In this paper, the recognition algorithm of the ramp event of wind speed and power is designed based on the Swinging Door Algorithm, and the algorithm parameters are taken as the time threshold 4h, wind speed threshold 6m s-1 and power threshold 1000kW. For the recognition of ramp events of other wind turbines, this paper suggests using 2/3 value of the difference between rated wind speed and cut-in wind speed as the wind speed threshold parameter and 2/3 value of rated power as the power threshold parameter. The terrain influence on the ramp event is significant, and the ramp event is more related to the altitude and average wind speed at the turbine, and the time proportion of the ramp event under different terrain is distributed in the range of 6.5% to 9.8%, with the average value of 7.8%.

Key words: Ramping event, detection method, Swinging Door Algorithm, wind farm

中图分类号:

P49
P412

梁志, 张哲, 师宇, 刘磊. 基于旋转门算法的风速和风功率爬坡事件的识别方法及特征分析^*[J]. 中国科学院大学学报, DOI: 10.7523/j.ucas.2023.014.

LIANG Zhi, ZHANG Zhe, SHI Yu, LIU Lei. Detection method and characterization of Ramp event of wind speed and wind power based on Swinging Door Algorithm[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas.2023.014.

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基于旋转门算法的风速和风功率爬坡事件的识别方法及特征分析^*

Detection method and characterization of Ramp event of wind speed and wind power based on Swinging Door Algorithm

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