摘要
以发电机5阶实用模型为研究对象,利用励磁电压参考值的变化产生动态响应,采用蚁群算法辨识同步发电机参数,分析干扰的大小和类型对发电机参数辨识的影响。在RTDS仿真机组上验证了蚁群算法的可行性,结果表明,从扰动的大小上看,扰动越大,参数辨识的精度越高;从扰动的类型上看,白噪声激励下辨识精度较好,该激励更有利于激发同步发电机的次暂态过程;无论是哪种扰动方式,稳态参数的精度没有大的变化,改善的主要是次暂态参数的辨识精度。
With the fifth order model of synchronous generator,the dynamic response of synchronous generator is generated by changing the excitation reference voltage,the synchronous generator parameters are identified by the ant colony optimization algorithm,and the influences of disturbance size and mode on identification accuracy are analyzed. The feasibility of ant colony optimization algorithm is verified on RTDS. Results show that,the larger the disturbance is,the higher the identification accuracy will be. As to the disturbance size mode,the identification accuracy is better when white noise is added,which more effectively stimulates the subtransient behavior of synchronous generator,and it improves the identification accuracy of subtransient parameters with little effect on that of steady-state parameters.
出处
《电力自动化设备》
EI
CSCD
北大核心
2009年第11期50-53,共4页
Electric Power Automation Equipment
基金
国家重点基础研究发展计划课题(2004CB217901)
国家杰出青年科学基金项目(50725723)~~
关键词
同步发电机
参数辨识
辨识精度
蚁群算法
白噪声
扰动方式
synchronous generator
parameter identification
identification accuracy
ant colony optimization algorithm
white noise
disturbance mode
