基于相关熵的光伏电池模型鲁棒参数辨识法
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摘要
参数辨识可以提高光伏电池模型参数设置的精确度,得到与实际对象相一致的模型。针对加权最小二乘参数辨识(WLS-PI)方法受测量数据显著误差影响显著的问题,提出了一种基于相关熵的鲁棒参数辨识(C-PI)方法。首先,分析了太阳能电池理论模型;其次,构造了一种相关熵估计器,通过该估计器的影响函数分析测量误差对辨识结果的影响,进一步将C-PI方法应用于光伏电池模型的参数辨识上。最后,将C-PI和WLS-PI两种方法用于仿真实例中,结果显示C-PI方法鲁棒性更好;进一步采用光伏电池的测试数据验证了C-PI方法的可行性与有效性。
Parameter identification can improve the accuracy of model parameters in the photovoltaic cell model,which can guarantee that the identified model is consistent with the actual plant.In this paper,considering the problem of the weighted least square based parameter identification(WLS-PI) method that the gross measurement errors severely bias the results of identification,a robust parameter identification method is proposed.First,the theoretical model of the photovoltaic cell is investigated.Secondly,the robustness of proposed correntropy estimator is analyzed by using the influence function,and then a correntropy based parameter identification(C-PI) method is developed for the photovoltaic cell model.Finally,the WLS-PI and C-PI methods are used in the simulation example.The results show that the C-PI method is more robust than WLS-PI method.The experimental data of the photovoltaic cell is also used to demonstrate the feasibility and effectiveness of C-PI method.
Parameter identification can improve the accuracy of model parameters in the photovoltaic cell model,which can guarantee that the identified model is consistent with the actual plant.In this paper,considering the problem of the weighted least square based parameter identification(WLS-PI) method that the gross measurement errors severely bias the results of identification,a robust parameter identification method is proposed.First,the theoretical model of the photovoltaic cell is investigated.Secondly,the robustness of proposed correntropy estimator is analyzed by using the influence function,and then a correntropy based parameter identification(C-PI) method is developed for the photovoltaic cell model.Finally,the WLS-PI and C-PI methods are used in the simulation example.The results show that the C-PI method is more robust than WLS-PI method.The experimental data of the photovoltaic cell is also used to demonstrate the feasibility and effectiveness of C-PI method.
引文
[1]张俊红,魏学业,祝天龙.光伏阵列建模和仿真特性研究[J].计算机仿真,2014,31(3):134-138.Zhang J H,Wei X Y,Zhu T L.Research on Modeling and Characteristic Simulation of Photovoltaic Array[J].Computer Simulation,2014,31(3):134-138.
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[14]简献忠,严军,范建鹏,等.基于差分进化算法的光伏阵列MPPT控制方法[J].控制工程,2014,21(4):559-562.Jian X Z,Yan J,Fan J P,et al.MPPT Control Method of Photovoltaic Array Based on Differential Evolution Algorithm[J]..Control Engineering of China,2014,21(4):559-562.
[15]Walker G.Evaluating MPPT Converter Topologies Using a MATLAB PV Model[J].Journal of Electrical&Electronics Engineering,2001,21(1):49-56.
[16]Liu W,Pokharel P P,Príncipe J C.Correntropy:Properties and Applications in Non-Gaussian Signal Processing[J].IEEETransactions on Signal Processing,2007,55(11):5286-5298.
[17]王明达,赵瑞杰.基于数据手册的光伏电池特性及参数实用估算方法[J].可再生能源,2012,30(3):102-107.Wang M D,Zhao R J.Practicable Approaches to Predicting PV Array Model Parameters and I-U Characteristics Based on Datasheet[J].Renewable Energy Resources,2012,30(3):102-107.
[2]周建良,王冰,张一鸣.基于实测数据的光伏阵列参数辨识与输出功率预测[J].可再生能源,2012,30(7):1-4.Zhou J L,Wang B,Zhang Y M.Parameter Identification and Output Power Prediction of Photovoltaic Array Based on the Measured Data[J].Renewable Energy Resources,2012,30(7):1-4.
[3]查晓锐,王冰,黄存荣,等.一种基于遗传算法的光伏阵列参数辨识方法[J].可再生能源,2012,32(8):1075-1080.Zha X R,Wang B,Huang C R,et al.A Parameter Identification Method of Photovoltaic Array Based on Genetic Algorithm[J].Renewable Energy Resources,2012,32(8):1075-1080.
[4]李宗鉴,陈玉玲,方伟超,等.基于有限测量信息的光伏模组模型参数辨识方法研究[C].第三十三届中国控制会议论文集(D卷),2014(07)TM615.Li Z J,Chen Y L,Fang W C.et al.Research on Parameter Identification Method Based on Finite Measurement Information for Photovoltaic Array Model[C].The 33rd Chinese Control Conference(D),2014(07)TM615.
[5]高金辉,苏军英,李迎迎.太阳电池模型参数求解算法的研究[J].太阳能学报,2012,33(9):1458-1462Gao J H,Su J Y,Li Y Y.Research on the Solving Algorithm of Solar Cell Model's Parameters[J].Acta Energiae Solaris Sinica,2012,33(9):1458-1462
[6]田琦,赵争鸣,韩晓艳.光伏电池模型的参数灵敏度分析和参数提取方法[J].电力自动化设备,2013,33(5):119-124Tian Q,Zhao Z M,Han X Y.Sensitivity Analysis and Parameter Extraction of Photovoltaic Cell Model[J].Electric Power Automation Equipment,2013,33(5):119-124
[7]郭亮,陈维荣,贾俊波,等.基于粒子群算法的BP神经网络光伏电池建模[J].电工电能新技术,2011,30(2):84-88.Guo L,Chen W R,Jia J B,et al.Modeling of Photovoltaic-Array Based on BP Neural Networks Improved by Particle Swarm Optimization Algorithm[J].Advanced Technology of Electrical Engineering and Energy,2011,30(2):84-88.
[8]师楠,周苏荃,李一丹,等.基于Bezier函数的光伏电池建模[J].电网技术,2015,39(8):2195-2200.Nan N,Zhou S Q,Li Y D et al.PV Cell Modeling Based on Bezier Function[J].Power System Technology,2015,39(8):2195-2200.
[9]李炜,朱新坚,曹广益.基于一种改进的BP神经网络光伏电池建模[J].计算机仿真,2006,23(7):228-230.Li W,Zhu X J,Cao G Y.Modeling of Photovoltaic-Array Based on Improved BP Neural Networks Identification[J].Computer Simulation,2006,23(7):228-230.
[10]张军朝,陈俊杰.粒子群优化RBF神经网络光伏电池建模研究[J].计算机工程与科学,2011,33(9):169-173.Zhang J C,Chen J J.Modeling Photovoltaic-Arrays Based on the REF Netural Networks Improved by Particle Swarm Optimization Algorithm[J].Computer Engineering&Science,2011,33(9):169-173.
[11]刘翼,荆龙,童亦斌.基于Simulink的光伏电池组件建模和MPPT仿真研究[J].科技导报,2010,28(18):94-97.Liu Y,Jing L,Tong Y B.Study of PV Module and MPPT Control Based on Simulink[J].Science&Technology Review,2010,28(18):94-97.
[12]Salmi T,Bouzguenda M,Gastli A,et al.Matlab/simulink based modeling of photovoltaic cell[J].International Journal of Renewable Energy Research(IJRER),2012,2(2):213-218.
[13]饶文培,沈安文,杨诚,等.基于改进的黄金分割法的光伏逆变器MPPT控制[J].控制工程,2012,19(6):1144-1150.Rao W P,Shen A W,Yang C.Maximum Power Point Tracking Based On Modified Golden-Section Search Method[J].Control Engineering of China,2012,19(6):1144-1150.
[14]简献忠,严军,范建鹏,等.基于差分进化算法的光伏阵列MPPT控制方法[J].控制工程,2014,21(4):559-562.Jian X Z,Yan J,Fan J P,et al.MPPT Control Method of Photovoltaic Array Based on Differential Evolution Algorithm[J]..Control Engineering of China,2014,21(4):559-562.
[15]Walker G.Evaluating MPPT Converter Topologies Using a MATLAB PV Model[J].Journal of Electrical&Electronics Engineering,2001,21(1):49-56.
[16]Liu W,Pokharel P P,Príncipe J C.Correntropy:Properties and Applications in Non-Gaussian Signal Processing[J].IEEETransactions on Signal Processing,2007,55(11):5286-5298.
[17]王明达,赵瑞杰.基于数据手册的光伏电池特性及参数实用估算方法[J].可再生能源,2012,30(3):102-107.Wang M D,Zhao R J.Practicable Approaches to Predicting PV Array Model Parameters and I-U Characteristics Based on Datasheet[J].Renewable Energy Resources,2012,30(3):102-107.