陈凌;韩伟;张经炜;

• 1:河海大学能源与电气学院
• 2:国网淮安供电公司

摘要(Abstract)：

对不同故障下光伏组件内部等效参数和外特性电气参数进行特征提取,分别采用改进人工鱼群算法优化径向基函数神经网络(improved artificial fish swarm algorithm-radical basic function neural network,IAFSA-RBFNN)算法和相关向量机(relevance vector machine,RVM)算法,建立了基于内部等效参数和外特性电气参数的4种光伏组件故障诊断模型,用于光伏组件的初步故障诊断。在此基础上,提出了一种基于改进证据相似度的光伏组件数据融合故障诊断模型,将上述4种模型的诊断结果作为该改进数据融合算法的基本概率分配(basic probability assignment,BPA)函数值,在决策层进行融合诊断输出,仿真和实验结果验证了上述方法可有效提高故障诊断的精度。

关键词(KeyWords)： 光伏组件;数据融合;径向基函数神经网络;相关向量机;故障诊断;改进证据相似度

Abstract:

Keywords:

基金项目(Foundation): 江苏省普通高校研究生科研创新计划(CXZZ12_0228)~~

作者(Author): 陈凌;韩伟;张经炜;

Email:

DOI: 10.13335/j.1000-3673.pst.2016.2294

参考文献(References)：

• [1]赵争鸣,刘建政,孙晓瑛,等.太阳能光伏发电及其应用[M].北京:科学出版社,2005:1-5.
• [2]魏学业,王立华,张俊红,等.光伏发电技术及其应用[M].北京:机械工业出版社,2013.
• [3]王元章,李智华,吴春华.光伏系统故障诊断方法综述[J].电源技术,2013,37(9):1700-1705.Wang Yuanzhang,Li Zhihua,Wu Chunhua.Fault diagnosis technologies for photovoltaic system[J].Chinese Journal of Power Sources,2013,37(9):1700-1705(in Chinese).
• [4]孔祥平,袁宇波,黄浩声,等.光伏电源故障电流的暂态特征及其影响因素[J].电网技术,2015,39(9):2444-2449.Kong Xiangping,Yuan Yubo,Huang Haosheng,et al.Fault current transient features and its related impact factors of PV generator[J].Power System Technology,2015,39(9):2444-2449(in Chinese).
• [5]Takashima T,Yamaguchi J,Ishida M.Disconnection detection using earth capacitance measurement in photovoltaic module string[J].Progress in Photovoltaics:Research and Applications,2008,16(8):669-677.
• [6]Chouder A,Silvestre S.Automatic supervision and fault detection of PV systems based on power losses analysis[J].Energy Conversion and Management,2010,51(10):1929-1937.
• [7]Wang W G,Liu A C,Chung H S,et al.Fault diagnosis of photovoltaic panels using dynamic current-voltage characteristics[J].IEEE Transactions on Power Electronics,2015,31(2):1588-1599.
• [8]韩伟,王宏华,王成亮,等.基于参数辨识的光伏组件故障诊断模型[J].电网技术,2015,39(5):1198-1204.Han Wei,Wang Honghua,Wang Chengliang,et al.Parameter identification based fault diagnosis model of photovoltaic modules[J].Power System Technology,2015,39(5):1198-1204(in Chinese).
• [9]王元章,李智华,吴春华,等.基于BP神经网络的光伏组件在线故障诊断[J].电网技术,2013,37(8):2094-2100.Wang Yuanzhang,Li Zhihua,Wu Chunhua,et al.A survey of online fault diagnosis for PV module based on BP neural network[J].Power System Technology,2013,37(8):2094-2100(in Chinese).
• [10]Hu Y H,Cao W P,Ma J,et al.Identifying PV module mismatch faults by a thermography-based temperature distribution analysis[J].IEEE Transactions on Device and Materials Reliability,2014,14(4):951-960.
• [11]Chao K H,Chen P Y,Wang M H,et al.An intelligent fault detection method of a photovoltaic module array using wireless sensor networks[J].International Journal of Distributed Sensor Networks,2014(1):1-12.
• [12]翟载腾.任意条件下光伏阵列的输出性能预测[D].合肥:中国科学技术大学,2008.
• [13]赵钒卿,谷廷坤,刘丹,等.光伏组件形状参数工程解析模型[J].电网技术,2015,39(6):1485-1490.Zhao Fanqing,Gu Tingkun,Liu Dan,et al.Shape parameter engineering analytical model of PV module[J].Power System Technology,2015,39(6):1485-1490(in Chinese).
• [14]韩伟,王宏华,陈凌,等.光伏组件参数拟合及输出特性研究[J].电力自动化设备,2015,35(9):100-107.Han Wei,Wang Honghua,Chen Ling,et al.Research on parameter fitting and output characteristics of PV module[J].Electric Power Automation Equipment,2015,35(9):100-107(in Chinese).
• [15]Tipping M E.Sparse Bayesian learning and the relevance vector machine[J].Journal of Machine Learning Research,2001,1(3):211-244.
• [16]易辉,梅磊,李丽娟,等.基于多分类相关向量机的水电机组振动故障诊断[J].中国电机工程学报,2014,34(17):2843-2850.Yi Hui,Mei Lei,Li Lijuan,et al.Vibration fault diagnosis for hydroelectric generating units using the multi-class relevance vector machine[J].Proceedings of the CSEE,2014,34(17):2843-2850(in Chinese).
• [17]马登武,范庚,张继军.相关向量机及其在故障诊断与预测中的应用[J].海军航空工程学院学报,2013(2):154-160.Ma Dengwu,Fan Geng,Zhang Jijun.Relevance vector machine and its applications in fault diagnosis and prognosis[J].Journal of Naval Aeronautical and Astronautical,2013(2):154-160(in Chinese).
• [18]尹金良,朱永利,俞国勤.相关向量机及其在变压器故障诊断中的应用[J].电力自动化设备,2012,32(8):130-134.Yin Jinliang,Zhu Yongli,Yu Guoqin.Relevance vector machine and its application in transformer fault diagnosis[J].Electric Power Automation Equipment,2012,32(8):130-134(in Chinese).
• [19]Dempster A P.Upper and lower probabilities induced by a multivalued mapping[J].Annals of Mathematical Statistics,1967,38(2):325-339.
• [20]Shafer G.A mathematical theory of evidence[M].Princeton:Princeton University Press,1976:78-99.
• [21]姜礼平,刘杨,胡伟文,等.基于支持度的改进证据合成方法[J].系统工程与电子技术,2014,36(8):1483-1487.Jiang Liping,Liu Yang,Hu Weiwen,et al.Research on improved evidence combination method based on support degree[J].Systems Engineering and Electronics,2014,36(8):1483-1487(in Chinese).
• [22]朱友清,周石琳,邹焕新.基于相容系数的冲突证据合成方法及评价准则[J].系统工程与电子技术,2014,36(6):1118-1123.Zhu Youqing,Zhou Shilin,Zou Huanxin.Combination method of conflict evidences and evaluation rule based on compatibility ratio[J].Systems Engineering and Electronics,2014,36(6):1118-1123(in Chinese).
• [23]张经炜,丁坤,卞新高,等.一种户外光伏组件测试平台研制[J].电子测量技术,2013,36(7):93-96.Zhang Jingwei,Ding Kun,Bian Xingao,et al.Development of PV module outdoor test platform[J].Electronic Measurement Technology,2013,36(7):93-96(in Chinese).