汽轮机及调节系统参数直接辨识法研究及应用
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摘要
针对目前汽轮机及其调节系统传统辨识方法存在的周期长、适应性差和辨识过程冗杂等问题,提出了一种直接辨识法。该辨识方法基于"最小二乘"思想,通过数值方法求解系统仿真值与实测值之间偏差最小时所对应的非线性方程,可快速准确地获得待辨识参数值。经过实际参数辨识试验,本文提出的直接辨识法的辨识过程效率高、辨识结果准确、鲁棒性强。该辨识方法为汽轮机及其调节系统参数辨识提供了一种新型有效手段。
Since most of the traditional parameter identification methods used in the steam turbine and its governing system have the shortages of poor fitness, complicated identification process and long period, a novel identification method based on least square theory, called direct identification method, is proposed in this paper. Parameter to be identified can be obtained quickly and accurately through direct identification method if the identification process is transferred to solve nonlinear equation which represents the minimal error between simulated data and measured data. The identification results show that during identification process the proposed method has high identification efficiency, accurate identification results and robust identification process compared with the traditional parameter identification method. The proposed identification method brings a novel way for steam turbine speed governor system identification.
Since most of the traditional parameter identification methods used in the steam turbine and its governing system have the shortages of poor fitness, complicated identification process and long period, a novel identification method based on least square theory, called direct identification method, is proposed in this paper. Parameter to be identified can be obtained quickly and accurately through direct identification method if the identification process is transferred to solve nonlinear equation which represents the minimal error between simulated data and measured data. The identification results show that during identification process the proposed method has high identification efficiency, accurate identification results and robust identification process compared with the traditional parameter identification method. The proposed identification method brings a novel way for steam turbine speed governor system identification.
引文
[1]Mehta A,Kaufman H,Ravi R.Turbine system identification:experimental results[C]//Decision and Control,1994.Proceedings of the,IEEE Conference on.1995,4:3593-3595.
[2]Shen M,Venkatasubramanian V,Abi-Samra N,et al.A new framework for estimation of generator dynamic parameters[J].IEEE Transactions on Power Systems,2000,15(2):756-763.
[3]王志群,朱守真,楼鸿祥,等.基于时域分段线性多项式法的大型汽轮机建模和参数辨识[J].中国电机工程学报,2003,23(4):128-133.WANG Zhi-qun,ZHU Shou-zhen,LOU Hong-xiang,et al.PLPF based modeling and parameter-identifying of large steam turbine in time domain[J].Proceedings of CSEE,2003,23(4):128-133.
[4]Stefopoulos G K,Georgilakis P S,Hatziargyriou N D,et al.A Genetic Algorithm Solution to the Governor-Turbine Dynamic Model Identification in Multi-Machine Power Systems[C]//Decision and Control,2005 and 2005 European Control Conference.Cdc-Ecc'05.IEEE Conference on.2006:1288-1294.
[5]苟小龙,张杰,王家胜,等.基于粒子群算法的汽轮机及其调速系统参数辨识方法[J].系统仿真学报,2014,26(7):1511-1516.GOU Xiao-long,ZHANG Jie,WANG Jia-sheng,et al.Parameter Identification Method of Steam Turbine and Its Speed Governor System Based on Particle Swarm Optimization[J].Journal of System Simulation,2014,26(7):1511-1516.
[6]Chaoshun Li,Li Chang,Zhengjun Huang,et al.Parameter identification of a nonlinear model of hydraulic turbine governing system with an elastic water hammer based on a modified gravitational search algorithm[J].Engineering Applications of Artificial Intelligence(S0952-1976),2016,50(4):177-191.
[7]Chaoshun Li,Zhou J,Xiao H,et al.Predictive control of hydraulic turbine with gravitational search based fuzzy model identification[J].Journal of Hydroelectric Engineering,2013,32(6):272-277.
[8]Chaoshun Li,Zhou J,Xiao J,et al.Hydraulic turbine governing system identification using T-S fuzzy model optimized by chaotic gravitational search algorithm[J].Engineering Applications of Artificial Intelligence:(S0952-1976),2013,26(9):2073-2082.
[9]张杰.一种应用于汽轮机及其调节系统的智能寻优参数辨识方法[D].重庆:重庆大学,2014.Zhang Jie.An Intelligent Optimization Parameter Identification Method Used in the Steam Turbine and its Governing System[D].Chongqing:Chongqing University,2014.
[2]Shen M,Venkatasubramanian V,Abi-Samra N,et al.A new framework for estimation of generator dynamic parameters[J].IEEE Transactions on Power Systems,2000,15(2):756-763.
[3]王志群,朱守真,楼鸿祥,等.基于时域分段线性多项式法的大型汽轮机建模和参数辨识[J].中国电机工程学报,2003,23(4):128-133.WANG Zhi-qun,ZHU Shou-zhen,LOU Hong-xiang,et al.PLPF based modeling and parameter-identifying of large steam turbine in time domain[J].Proceedings of CSEE,2003,23(4):128-133.
[4]Stefopoulos G K,Georgilakis P S,Hatziargyriou N D,et al.A Genetic Algorithm Solution to the Governor-Turbine Dynamic Model Identification in Multi-Machine Power Systems[C]//Decision and Control,2005 and 2005 European Control Conference.Cdc-Ecc'05.IEEE Conference on.2006:1288-1294.
[5]苟小龙,张杰,王家胜,等.基于粒子群算法的汽轮机及其调速系统参数辨识方法[J].系统仿真学报,2014,26(7):1511-1516.GOU Xiao-long,ZHANG Jie,WANG Jia-sheng,et al.Parameter Identification Method of Steam Turbine and Its Speed Governor System Based on Particle Swarm Optimization[J].Journal of System Simulation,2014,26(7):1511-1516.
[6]Chaoshun Li,Li Chang,Zhengjun Huang,et al.Parameter identification of a nonlinear model of hydraulic turbine governing system with an elastic water hammer based on a modified gravitational search algorithm[J].Engineering Applications of Artificial Intelligence(S0952-1976),2016,50(4):177-191.
[7]Chaoshun Li,Zhou J,Xiao H,et al.Predictive control of hydraulic turbine with gravitational search based fuzzy model identification[J].Journal of Hydroelectric Engineering,2013,32(6):272-277.
[8]Chaoshun Li,Zhou J,Xiao J,et al.Hydraulic turbine governing system identification using T-S fuzzy model optimized by chaotic gravitational search algorithm[J].Engineering Applications of Artificial Intelligence:(S0952-1976),2013,26(9):2073-2082.
[9]张杰.一种应用于汽轮机及其调节系统的智能寻优参数辨识方法[D].重庆:重庆大学,2014.Zhang Jie.An Intelligent Optimization Parameter Identification Method Used in the Steam Turbine and its Governing System[D].Chongqing:Chongqing University,2014.