基于深度学习的异步风力发电机组功率振荡抑制方法
Deep Learning Based Power Oscillation Suppression Method for Asynchronous Wind Turbine Generators
邓森 1黄宝成 1胡从星 1杨朋雨1
作者信息
- 1. 国家电投集团江苏电力有限公司,江苏南京 210000
- 折叠
摘要
由于引起异步风力发电机组功率振荡的因素较多,难以保障功率振荡抑制的效果,为此,提出基于深度学习的异步风力发电机组功率振荡抑制方法的研究.从风力机动态特性、发电机组动态特性以及传动链动态特性 3个角度分析了异步风力发电机组功率振荡状态,借助长短期记忆网络实现对振荡的有效抑制.在测试结果中,设计的振荡抑制方法应用效果不仅更高效,且对于基础振荡幅度的控制效果更好.
Abstract
Due to the numerous factors that cause power oscillation in asynchronous wind turbines,the effectiveness of power oscillation suppression is difficult to guarantee.Therefore,a deep learning based method for suppressing power oscillation in asynchronous wind turbines is proposed.After analyzing the power oscillation state of asynchronous wind turbines from three perspectives:Dynamic characteristics of wind turbines,dynamic characteristics of generator units,and dynamic characteristics of transmission chains,effective suppression of oscillation is achieved through the use of long short-term memory networks.In the test results,the application effect of designing oscillation suppression methods is not only more efficient,but also better for controlling the basic oscillation amplitude.
关键词
深度学习/异步风力发电机组/功率振荡抑制/风力机动态特性/发电机组动态特性/传动链动态特性Key words
deep learning/asynchronous wind turbine generators/power oscillation suppression/dynamic characteristics of wind turbines/dynamic characteristics of generator units/dynamic characteristics of the transmission chain引用本文复制引用
出版年
2024
NETL
NSTL
万方数据