微型电脑应用2023，Vol.39Issue(12)：73-76,4.
基于机器学习的分布式发电并网保护研究
Research on Distributed Generation Grid Connection Protection Based on Machine Learning
摘要
Abstract
As the access and exit of distributed generation occur at any time,the impact on the power grid is more complex.In order to ensure the stable operation of distributed generation grid connected system,a method of distributed generation grid connected protection based on machine learning is proposed.In view of the fault,disturbance and islanding events in the grid connected distributed generation system,the support vector machine in the machine learning algorithm is used to establish a classifier model to classify and detect the above events.The coordinated control strategy of dual filtering is designed to improve the power stability of distributed generation grid connection under disturbance events and fault events.By a variable coefficient droop control strategy,the DC bus voltage of the system is controlled to improve the current quality of the system during islan-ding operation.The experimental results show that the proposed method can effectively control the power of distributed genera-tion grid connection and maintain the current stability,have good event identification ability and protection ability.关键词
机器学习/支持向量机/双重滤波/分布式发电并网/下垂控制Key words
machine learning/support vector machine/dual filtering/grid connection of distributed power generation/sag con-trol分类
信息技术与安全科学引用本文复制引用
白明辉,袁绍军..基于机器学习的分布式发电并网保护研究[J].微型电脑应用,2023,39(12):73-76,4.基金项目
国网河北供电公司2020承载力调度三类分布式调度管理系统正常项目(GNRX202100643) （GNRX202100643）
