摘要
普通水轮机调节系统多采用中值滤波,其在电站实际运用中针对随机噪声效果不理想,所以在研究PID算法的同时需要在测频电路中加入更为先进的随机噪声过滤算法,自适应的卡尔曼滤波擅长滤除随机噪声,但传统卡尔曼滤波算法中要求干扰噪声方差矩阵Q和测量噪声方差矩阵R为已知量,这一点难以在水电机组实际运行的情况下办到,文中引入一种基于RTQC(原始的实时质量控制方法)算法改进的卡尔曼滤波,结合了RTQC算法实时误差处理能力强和卡尔曼滤波自适应的特点,将其应用到水力发电机组的测频电路中,可以使水轮机调节系统测频的抗干扰性能大幅提高。
Median filtering is generally used in the regulation system of general hydro turbine,but its application result in the actual hydro-power station is not good thanks to its poor random noise treatment.Therefore while studying the PID algorithm,more advanced random noise filter algorithm should be added to the measuring frequency circuit.The adaptive Kalman filter algorithm is good at filtering random noises but the traditional Kalman filter algorithm requires that both the interference noise variance matrix Q and the measurement noise variance matrix R be known,which is almost impossible in the actual operation of the station.In this paper,we introduce a RTQC(the original method of real time quality control)-based improved Kalman filtering,which is applied in the frequency measurement circuit of the hydro generating unit together with the real time error handling ability and characteristics of adaptive Kalman filtering,resulting in substantial improvement of the anti-jamming performance of the frequency measurement of the hydro-turbine governing system.
出处
《电网与清洁能源》
北大核心
2017年第1期137-142,共6页
Power System and Clean Energy
基金
重庆市教委科学技术研究项目(KJ1501105)~~
关键词
水轮机调节系统
频率测量
卡尔曼滤波
水力发电
RTQC算法
hydro turbine regulating system
frequency-measurement
kalman filter hydroelectric
RTQC algorithm