基于谐波小波的风力发电并网电压故障信号特征检测
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摘要
针对风力发电并网对电网电能质量产生影响的问题,深入分析风力发电并网特点及故障特征,提出一种采用谐波小波降噪与时频联合分析相结合的风力发电并网电压故障信号特征提取方法,该方法解决了采用传统的傅里叶变换无法对非平稳电压故障测试信号进行分析处理的问题,充分利用谐波小波降噪技术对强噪声背景下的非平稳电压故障测试信号进行提纯降噪处理,再对降噪后的纯净信号进行时频联合分析,利用时频联合分析结果对风力发电并网电压故障进行精确定位,从而为故障穿越提供必要的参考决策,最后通过仿真和实验验证了该方法的有效性。
Aiming at solve the problem of the power quality influence by wind power integration,the integration characteristics and fault characteristics of wind power station is the thorough analysis,a novel method is proposed in this paper,the method makes combination with harmonic wavelet noise reduction and time-frequency joint analysis,and it is used for voltage fault signal feature extraction of wind power integration,this method has solved the problems that the traditional Fourier transform can′t process the fault testing signal with non-stationary character.The method makes full use of harmonic wavelet noise reduction technology for purification of non-stationary voltage fault test signal in strong noise,and then the time-frequency combined analysis is used to accurately locate the voltage fault of wind power integration,the method is able to provide necessary reference decision for fault crossing.Finally,the effectiveness of the method is verified by simulation and experiment.
Aiming at solve the problem of the power quality influence by wind power integration,the integration characteristics and fault characteristics of wind power station is the thorough analysis,a novel method is proposed in this paper,the method makes combination with harmonic wavelet noise reduction and time-frequency joint analysis,and it is used for voltage fault signal feature extraction of wind power integration,this method has solved the problems that the traditional Fourier transform can′t process the fault testing signal with non-stationary character.The method makes full use of harmonic wavelet noise reduction technology for purification of non-stationary voltage fault test signal in strong noise,and then the time-frequency combined analysis is used to accurately locate the voltage fault of wind power integration,the method is able to provide necessary reference decision for fault crossing.Finally,the effectiveness of the method is verified by simulation and experiment.
引文
[1]中国产业发展研究网.2017年全球风电行业新增装机容量、累计装机容量及占比前景预测[EB/OL].http://chinaidr.com/tradenews/2017-07/114576.html,2017-07-25/2018-10-01.
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[14]包广清,宋泽,吴国栋,等.基于经验模态分解和形态学的风电并网电压故障检测[J].农业工程学报,2016,32(11):219-225.
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[2]孙涛,王伟胜,戴慧珠,等.风力发电引起的电压波动和闪变[J].电网技术,2003,27(12):62-66.
[3]郭琳,王萍,王慧慧,等.风力发电并网电压扰动信号的分析与检测[J].电源学报,2015,13(5):15-21.
[4]胡家兵,孙丹,贺益康,等.电网电压骤降故障下双馈风力发电机建模与控制[J].电力系统自动化,2006(8):21-26.
[5]孙元章,吴俊,李国杰.风力发电对电力系统的影响[J].电网技术,2007,31(20):55-62.
[6]BOLLEN M H J, OLGUIN G, MARTINS M.Voltage dips at the terminals of wind power installations[J].Wind Energy,2010,8(3):307-318.
[7]SUN T,CHEN Z,BLAABJERG F.Voltage recovery of grid-connected wind turbines with DFIG after a short-circuit fault[C].Power Electronics Specialists Conference,IEEE,2004:1991-1997.
[8]ABBEY C,JOOS G.Effect of low voltage ride through(LVRT)characteristic on voltage stability[C].IEEE Power Engineering Society General Meeting,2005:1901-1907.
[9]张兴,张龙云,杨淑英,等.风力发电低电压穿越技术综述[J].电力系统及其自动化学报,2008,20(2):1-8.
[10]胡家兵,孙丹,贺益康,等.电网电压骤降故障下双馈风力发电机建模与控制[J].电力系统自动化,2006(8):21-26.
[11]李加升,杨金辉,吴顺秋.风能发电并网时引起的电压波动与闪变检测的仿真研究[C]电磁测量技术、标准、产品国际研讨及展会,2010.
[12]王丽霞.基于信号处理的电能质量扰动检测与识别[D].成都:西南交通大学,2010.
[13]李从飞.电能质量扰动检测与分类方法研究[D].芜湖:安徽工程大学,2017.
[14]包广清,宋泽,吴国栋,等.基于经验模态分解和形态学的风电并网电压故障检测[J].农业工程学报,2016,32(11):219-225.
[15]凌玲,徐政.基于数学形态学的动态电能质量扰动的检测与分类方法[J].电网技术,2006,30(5):62-66.
[16]国家发展和改革委员会,国家能源局.风电发展“十三五”规划[R].2016.
[17]国家能源局.关于可再生能源发展“十三五”规划实施的指导意见(国能发新能[2017]31号)[R].2017.