基于主成分分析和马氏距离的光伏系统健康状态研究
|
摘要
为准确评估光伏系统的性能状态,保障电网的安全运行,首先,以预测与健康管理技术为基础,利用多元统计分析理论,建立基于主成分分析和马氏距离的光伏系统健康状态评估方法,采用主成分分析对原始多维输入变量进行预处理,利用马氏距离表征光伏系统的健康程度;然后,通过旁路实验和模拟灰尘实验验证了该光伏系统健康状态评估方法能够避免PR方法评价结果的"伪正常"现象;最终,通过实验对该光伏系统健康状态评估方法与PR方法进行对比分析。研究结果表明,与PR方法相比,该光伏系统健康状态评估方法能够更加灵敏、准确地反映光伏系统的性能状态。
In order to evaluate PV system performance more accurately and ensure the safety of power grid, first, a PCA-MD evaluation method of photovoltaic system heath state is put forward based on PHM technology and multivariate statistical analysis. The PCA is used to preprocess original multi-dimensional input variables and the MD is used to show health degree of PV system. Then, the PCA-MD method is testified by bypass experiments and dust shelter experiments. The experiments results show that the PCA-MD method could avoid the "pseudo normal" results of PR method effectively. Finally, the contrast experiments is designed to show the difference of PCA-MD method and PR method and the outcome demonstrates that the PCA-MD method is more sensitive and accurate than PR method.
In order to evaluate PV system performance more accurately and ensure the safety of power grid, first, a PCA-MD evaluation method of photovoltaic system heath state is put forward based on PHM technology and multivariate statistical analysis. The PCA is used to preprocess original multi-dimensional input variables and the MD is used to show health degree of PV system. Then, the PCA-MD method is testified by bypass experiments and dust shelter experiments. The experiments results show that the PCA-MD method could avoid the "pseudo normal" results of PR method effectively. Finally, the contrast experiments is designed to show the difference of PCA-MD method and PR method and the outcome demonstrates that the PCA-MD method is more sensitive and accurate than PR method.
引文
[1]IEC61724-1998,Photovoltaic System Performance Monitoring-guidelines for Measurement,Data Exchange and Analysis(2006)[S].
[2]GB20513-2006,光伏系统性能检测、测量、数据交换和分析导则(2006版)[S].GB20513-2006,Photovoltaic System Performance Monitoring-guidelines for Measurement,Data Exchange and Analysis(2006)[S].
[3]Takashi Oozeki,Kenji Otani,Kosuke Kurokawa.An evaluation method for PV system to identify system losses by means of utilizing monitoring data[A].Conference Record of 2006 IEEE 4th World Conference on Photovoltaic Energy Conversion[C].Hawaii:Curran Associates,2006.2319-2322.
[4]李芬,陈正洪.并网光伏系统性能精细化评估方法研究[J].太阳能学报,2013,34(6):974-983.Li Fen,Chen Zhenghong.Refinement assessment method of grid-connected PV system performance[J].Acta Energiae Solaris Sinica,2013,34(6):974-983.
[5]Michael Pecht,Kang Rui.Diagnostics,Prognostics and System's Health Management[M].Hong Kong:City University of Hong Kong,2010.
[6]上海航空测控技术研究所.航空故障诊断与健康管理技术[M].北京:航空工业出版社,2010.AVIC Shanghai Aeronautical Measurement-controlling Research Institute.Aviation Fault Diagonsis and Health Management Technology[M].Beijing:China Aviation Publishing Press,2010.
[7]George Vachtsevanos,Frand Lewis,Michael Roemer.Intelligent Fault Diagnosis and Prognosis for Engineering Systems[M].New York:John Wiley&Sons,2007.
[8]商立群,王守鹏.改进主成分分析法在火电机组综合评价中的应用[J].电网技术,2014,38(7):1928-1933.Shang Liqun,Wang Shoupeng.Application of improved principal component analysis in comprehensive assessment on thermal power generation units[J].Power System Technology,2014,38(7):1928-1933.
[9]张翔,徐洪平,安雪岩,等.基于马氏距离的液体火箭发动机稳态过程故障程度评估方法[J].计算机测量与控制,2015,23(8):2745-2748.Zhang Xiang,Xu Hongping,An Xueyan,et al.Discussion on fault degree assessment method for steady process of liquid propellant rocket engine based on mahalanobis distance[J].Computer Measurement&Control,2015,23(8):2745-2748.
[10]何晓群.多元统计分析[M].北京:中国人民大学出版社,2004.He Xiaoqun.Multivariate Statistical Analysis[M].Beijing:China Renmin University Publishing Press,2004.
[11]周鹏飞,白玉红.基于PCA和DEA的海上可再生能源开发综合评价[J].可再生能源,2014,32(1):120-126.Zhou Pengfei,Bai Yuhong.PCA and DEA based comprehensive evaluation on the exploiture of marine renewable energy[J].Renewable Energy Resources,2014,32(1):120-126.
[12]杨云宝,黄铭,李丹,等.海堤安全监测的马氏距离判别方法[J].水利科技与经济,2013,19(3):109-113.Yang Yunbao,Huang Ming,Li Dan,et al.Evaluation of seawall safety monitoring base on mahalanobis distance method[J].Water Conservancy Science and Technology and Economy,2013,19(3):109-113.
[13]丁坤,张经炜,翟泉新,等.基于S-Function Builder的光伏阵列仿真模型[J].电网与清洁能源,2014,30(5):66-69.Ding Kun,Zhang Jingwei,Zhai Quanxin,et al.Simulation model for PV arrays based on S-Function Builder[J].Power System and Clean Energy,2014,30(5):66-69.
[14]苏建徽,余世杰,赵为,等.硅太阳电池工程用数学模型[J].太阳能学报,2001,22(4):409-412.Su Jianhui,Yu Shijie,Zhao Wei,et al.Investigation on engineering analytical model of silicon solar cells[J].Acta Energiae Solaris Sinica,2001,22(4):409-412.
[15]丁坤,翟泉新,张经纬,等.一种光伏组件输出功率的估算模型[J].可再生能源,2014,32(3):275-278.Ding Kun,Zhai Quanxin,Zhang Jingwei,et al.An estimation model for PV module output power[J].Renewable Energy Resources,2014,32(3):275-278.
[2]GB20513-2006,光伏系统性能检测、测量、数据交换和分析导则(2006版)[S].GB20513-2006,Photovoltaic System Performance Monitoring-guidelines for Measurement,Data Exchange and Analysis(2006)[S].
[3]Takashi Oozeki,Kenji Otani,Kosuke Kurokawa.An evaluation method for PV system to identify system losses by means of utilizing monitoring data[A].Conference Record of 2006 IEEE 4th World Conference on Photovoltaic Energy Conversion[C].Hawaii:Curran Associates,2006.2319-2322.
[4]李芬,陈正洪.并网光伏系统性能精细化评估方法研究[J].太阳能学报,2013,34(6):974-983.Li Fen,Chen Zhenghong.Refinement assessment method of grid-connected PV system performance[J].Acta Energiae Solaris Sinica,2013,34(6):974-983.
[5]Michael Pecht,Kang Rui.Diagnostics,Prognostics and System's Health Management[M].Hong Kong:City University of Hong Kong,2010.
[6]上海航空测控技术研究所.航空故障诊断与健康管理技术[M].北京:航空工业出版社,2010.AVIC Shanghai Aeronautical Measurement-controlling Research Institute.Aviation Fault Diagonsis and Health Management Technology[M].Beijing:China Aviation Publishing Press,2010.
[7]George Vachtsevanos,Frand Lewis,Michael Roemer.Intelligent Fault Diagnosis and Prognosis for Engineering Systems[M].New York:John Wiley&Sons,2007.
[8]商立群,王守鹏.改进主成分分析法在火电机组综合评价中的应用[J].电网技术,2014,38(7):1928-1933.Shang Liqun,Wang Shoupeng.Application of improved principal component analysis in comprehensive assessment on thermal power generation units[J].Power System Technology,2014,38(7):1928-1933.
[9]张翔,徐洪平,安雪岩,等.基于马氏距离的液体火箭发动机稳态过程故障程度评估方法[J].计算机测量与控制,2015,23(8):2745-2748.Zhang Xiang,Xu Hongping,An Xueyan,et al.Discussion on fault degree assessment method for steady process of liquid propellant rocket engine based on mahalanobis distance[J].Computer Measurement&Control,2015,23(8):2745-2748.
[10]何晓群.多元统计分析[M].北京:中国人民大学出版社,2004.He Xiaoqun.Multivariate Statistical Analysis[M].Beijing:China Renmin University Publishing Press,2004.
[11]周鹏飞,白玉红.基于PCA和DEA的海上可再生能源开发综合评价[J].可再生能源,2014,32(1):120-126.Zhou Pengfei,Bai Yuhong.PCA and DEA based comprehensive evaluation on the exploiture of marine renewable energy[J].Renewable Energy Resources,2014,32(1):120-126.
[12]杨云宝,黄铭,李丹,等.海堤安全监测的马氏距离判别方法[J].水利科技与经济,2013,19(3):109-113.Yang Yunbao,Huang Ming,Li Dan,et al.Evaluation of seawall safety monitoring base on mahalanobis distance method[J].Water Conservancy Science and Technology and Economy,2013,19(3):109-113.
[13]丁坤,张经炜,翟泉新,等.基于S-Function Builder的光伏阵列仿真模型[J].电网与清洁能源,2014,30(5):66-69.Ding Kun,Zhang Jingwei,Zhai Quanxin,et al.Simulation model for PV arrays based on S-Function Builder[J].Power System and Clean Energy,2014,30(5):66-69.
[14]苏建徽,余世杰,赵为,等.硅太阳电池工程用数学模型[J].太阳能学报,2001,22(4):409-412.Su Jianhui,Yu Shijie,Zhao Wei,et al.Investigation on engineering analytical model of silicon solar cells[J].Acta Energiae Solaris Sinica,2001,22(4):409-412.
[15]丁坤,翟泉新,张经纬,等.一种光伏组件输出功率的估算模型[J].可再生能源,2014,32(3):275-278.Ding Kun,Zhai Quanxin,Zhang Jingwei,et al.An estimation model for PV module output power[J].Renewable Energy Resources,2014,32(3):275-278.