小波分析在电力负荷数据处理中的应用
|
摘要
电力负荷数据是电力大数据的核心内容,也是电力系统调度和规划等部门进行决策的重要参考依据。但由于各种不可控因素,原始负荷数据往往存在奇异点和噪声,同时巨量的负荷数据也会给数据存储和管理工作带来困难。为了解决这些问题,运用小波理论探讨了利用小波处理电力负荷数据的可行性,提出了小波双层阈值法,并结合实际案例,给出了小波分析在电力负荷数据去噪和压缩方面的应用。
Power load data is the core content of the power big data,and it is also an important reference for the decision-making of the dispatching and planning departments of the power system.However,due to various uncontrollable factors,original load data often have singularity and noise.At the same time,huge amounts of load data also bring difficulties to data storage and management.In order to solve these problems,mathematical basis of wavelet theory is analyzed,feasibility of using wavelet processing power load data is discussed,the double threshold method is put forward,application of wavelet analysis in the power load data denoising and compression is given combined with actual cases.
Power load data is the core content of the power big data,and it is also an important reference for the decision-making of the dispatching and planning departments of the power system.However,due to various uncontrollable factors,original load data often have singularity and noise.At the same time,huge amounts of load data also bring difficulties to data storage and management.In order to solve these problems,mathematical basis of wavelet theory is analyzed,feasibility of using wavelet processing power load data is discussed,the double threshold method is put forward,application of wavelet analysis in the power load data denoising and compression is given combined with actual cases.
引文
[1]徐谋.基于小波分析的输电线路故障诊断[D].武汉:武汉理工大学,2006.
[2]任震,黄雯莹,何建军,等.小波分析及其在电力系统中的应用(一)概论[J].电力系统自动化,1997,21(1):5-7,17.
[3]衡彤.小波分析及其应用研究[D].成都:四川大学,2003.
[4]朱希安,金声震,宁书年,等.小波分析的应用现状及展望[J].煤田地质与勘探,2003,31(2):51-55.
[5]孔玲军,王峰松.MATLAB小波分析超级学习手册[M].北京:人民邮电出版社,2014.
[6]刘毅华,赵光宙.故障分析中的小波软阈值改进除噪方法[J].继电器,2004,32(24):15-20.
[7]MALLAT S,HWANG W L.Singularity detection and processing with wavelets[J].IEEE Trans Information Theory,1992,38(2):617-643.
[8]DONOHO D L,JOHNSTONE I M.Adapting to unknown smoothness via wavelet shrinkage[J].Journal of the American Statistical Association,1995,90:1 200-1 224.
[9]王成栋,朱永生,张优云.转子振动信号消噪方法研究[J].振动、测试与诊断,2003,23(4):252-255.
[10]祝海龙,郭天佑,屈梁生.基于二进小波变换和软阈值改进的信号消噪[J].自动化学报,2004,30(2):199-207.
[11]秦毅,王家序,毛永芳.基于软阈值和小波模极大值重构的信号降噪[J].振动、测试与诊断,2011,31(5):543-547.
[2]任震,黄雯莹,何建军,等.小波分析及其在电力系统中的应用(一)概论[J].电力系统自动化,1997,21(1):5-7,17.
[3]衡彤.小波分析及其应用研究[D].成都:四川大学,2003.
[4]朱希安,金声震,宁书年,等.小波分析的应用现状及展望[J].煤田地质与勘探,2003,31(2):51-55.
[5]孔玲军,王峰松.MATLAB小波分析超级学习手册[M].北京:人民邮电出版社,2014.
[6]刘毅华,赵光宙.故障分析中的小波软阈值改进除噪方法[J].继电器,2004,32(24):15-20.
[7]MALLAT S,HWANG W L.Singularity detection and processing with wavelets[J].IEEE Trans Information Theory,1992,38(2):617-643.
[8]DONOHO D L,JOHNSTONE I M.Adapting to unknown smoothness via wavelet shrinkage[J].Journal of the American Statistical Association,1995,90:1 200-1 224.
[9]王成栋,朱永生,张优云.转子振动信号消噪方法研究[J].振动、测试与诊断,2003,23(4):252-255.
[10]祝海龙,郭天佑,屈梁生.基于二进小波变换和软阈值改进的信号消噪[J].自动化学报,2004,30(2):199-207.
[11]秦毅,王家序,毛永芳.基于软阈值和小波模极大值重构的信号降噪[J].振动、测试与诊断,2011,31(5):543-547.