基于灰狼优化算法和EEMD的水轮机调节系统强噪声环境在线辨识方法研究
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摘要
提出了一种基于灰狼优化算法和EEMD分解的水轮机调节系统强噪声环境下的在线辨识方法,通过EEMD的抗噪分解能力,对调节系统在线扰动下的实测功率进行分解,得到有效分量后,采用灰狼优化对水轮机调节系统进行参数辨识,并将上述方法在东江水电厂现场实际调节系统进行了参数建模应用。研究结果表明该方法能够有效的抑制现场实测信号中的噪声成分,并获得高精度的优化辨识参数,对水电机组的高精度控制和电力系统仿真分析的工程应用有一定的指导意义。
A kind of on-line identification method for hydraulic turbine governing system in strong noise environment is proposed based on gray wolf optimization algorithm and EEMD decomposition. By using the anti-noise decomposition ability of EEMD,the measured power of governing system under on-line disturbance is decomposed,and after obtaining the effective component,the grey wolf optimization is used to identify the parameters of hydraulic turbine governing system. The method is applied to the governing system of Dongjiang Hydropower Plant. The results show that the method can effectively suppress the noise components of field measured signals,and obtain high precision identification parameters,which has certain guiding significance on the high precision control of hydropower plant and the simulation and analysis of power system.
A kind of on-line identification method for hydraulic turbine governing system in strong noise environment is proposed based on gray wolf optimization algorithm and EEMD decomposition. By using the anti-noise decomposition ability of EEMD,the measured power of governing system under on-line disturbance is decomposed,and after obtaining the effective component,the grey wolf optimization is used to identify the parameters of hydraulic turbine governing system. The method is applied to the governing system of Dongjiang Hydropower Plant. The results show that the method can effectively suppress the noise components of field measured signals,and obtain high precision identification parameters,which has certain guiding significance on the high precision control of hydropower plant and the simulation and analysis of power system.
引文
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[2]刘昌玉,何雪松,李崇威,等.用于水轮机-引水管道参数辨识的改进型人工鱼群算法[J].电力自动化设备,2013,33(11):54-58.
[3]朱道利,别雄波.基于NNARX水轮机调节系统辨识的预测控制与故障诊断[J].自动化与仪器仪表,2017(12):228-230.
[4]庄明.基于遗传算法与文持向量回归的水轮机综合特性建模研究[J].水力发电,2016,42(12):81-84.
[5]陈帝伊,杨朋超,马孝义,等.水轮机调节系统的混沌现象分析及控制[J].中国电机工程学报,2011,31(14):113-120.
[6]陈晓勇,张太祥,王新乐,等.浅谈水电厂调速系统建模参数辨识试验[J].水电与抽水蓄能,2013,37(1):4-8.
[7]巩宇.抽水蓄能机组原动机及调节系统参数实测与建模研究[J].水电站机电技术,2011,34(4):9-14.
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[9]刘俊敏,李兴源,王曦,等.基于改进矩阵束算法的水轮机控制系统参数辨识[J].大电机技术,2015(2):60-64.
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