抽蓄电站励磁系统智能起励方式研究  

An Intelligent Excitation Method for Excitation System in Pumped Storage Power Stations

作　　者：柳炀 王瑞清 高向鹏 胡静宪 LIU Yang;WANG Ruiqing;GAO Xiangpeng;HU Jingxian(Nengshida Electric Co.,Ltd.,Wuhan 430070,China)

机构地区：[1]能事达电气股份有限公司,湖北武汉430070

出　　处：《水电与新能源》2025年第2期38-41,共4页Hydropower and New Energy

摘　　要：针对抽蓄机组励磁系统阳极电源主要采用他励的特点,在常规水电机组励磁系统采用的“软起励”方式的基础上,增加控制角直接起励的方式,采用AI神经网络算法,智能判断和选择起励方式和参数,实现自优化,自学习,可极大地提高抽蓄机组励磁系统的可靠性与效率。The anode power supply of the excitation system in pumped storage units mainly adopts separate excitation mode.On the basis of the“soft excitation”method adopted in the excitation system of conventional hydropower units,direct control angel excitation method is added.Then,AI neural network algorithm is used to intelligently judge and select the excitation method and parameters,which realizes self-optimization and self-learning.The intelligent excitation method greatly improves the reliability and efficiency of the excitation system of pumped storage units.

关 键 词：抽水蓄能电站 励磁系统 起励方式 他励 自并励 神经网络 

分 类 号：TM612[电气工程—电力系统及自动化]