基于贝叶斯推理的风电机组风轮偏航协同智能控制方法
Collaborative intelligent control method for wind turbine rotor yaw based on Bayesian inference
邬伟骏 1吴江波 1周强 1姜文兵1
作者信息
- 1. 国家电投集团江西赣州新能源有限公司,江西 赣州 330000
- 折叠
摘要
风向的变化对风电机组的偏航控制是一个挑战.对于风向的频繁变化,如果风电机组的反应速度过慢,无法及时调整偏航角度,将会影响发电效率.为了准确控制风电机组风轮偏航问题,文章提出了一种基于贝叶斯推理的风电机组风轮偏航协同智能控制方法.在考虑风速随机性的情况下,分析风向信号,获取风向样本数据.引入贝叶斯分类器,结合风向正态分析模型,计算服从上一批样本分布的风向样本后验概率,将其作为警戒值调节基准,建立基于贝叶斯推理的网络警戒值调节机制,通过爬山算法调节警戒值,完成风电机组风轮偏航协同智能控制.实验结果表明,所提方法对风电机组风轮偏航展开协同智能控制后,机舱位置出现偏航的次数为0,且偏航控制时间短,表明该方法可以完成风电机组风轮偏航协同智能控制.
Abstract
The change in wind direction poses a challenge to the yaw control of wind turbines.Due to frequent changes in wind direction,the response speed of wind turbines is too slow,making it difficult to adjust the yaw angle in a timely manner,thereby affecting power generation efficiency.In order to accurately control the problem of wind turbine wheel yaw,a collaborative intelligent control method for wind turbine wheel yaw considering the randomness of wind speed is proposed.Considering the randomness of wind speed,analyze the wind direction signal and obtain wind direction sample data.Introduce a Bayesian classifier and combine it with a wind direction normal analysis model to calculate the posterior probability of wind direction samples that follow the distribution of the previous batch of samples.Use it as the benchmark for adjusting the warning value,establish a network warning value adjustment mechanism based on Bayesian inference,and adjust the warning value through a mountain climbing algorithm to achieve collaborative intelligent control of wind turbine rotor yaw.The experimental results show that the proposed method achieves collaborative intelligent control of wind turbine rotor yaw,with zero occurrence of yaw in the cabin position and a short yaw control time.This indicates that the method can achieve collaborative intelligent control of wind turbine rotor yaw.
关键词
考虑风速随机性/风电机组/风轮偏航/协同智能控制Key words
consider the randomness of wind speed/wind turbines/wind wheel yaw/collaborative intelligent control引用本文复制引用
基金项目
国家电投总部科技项目(KYTC2021SD14)
出版年
2024
国家科技期刊平台
NSTL
万方数据