电能质量暂态信号检测及谐波源定位方法研究
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摘要
对电能质量问题的研究,是电力系统研究领域的重要前沿。电力系统中非线性负荷的日益增多,电能质量问题对电网和配电系统造成的直接危害和可能对人类生活和生产造成的损失也越来越大,电能质量直接关系到国民经济的总体效益。由于各种原因,在供电可靠性和电网电压幅度的稳定水平等指标上,我国的情况尤其落后。如何提高和保证电能质量,已成为国内外电工领域迫切需要解决的重要课题之一。
本论文对电能质量问题的分类以及各类电能质量问题的特征进行了综述。论文采用二进正交小波变换的方法、多分辨分析方法以及功率突变法等分析方法对各类短时电能质量扰动信号进行分析,设计出一种基于二进小波分析的计算方法,用于检测暂态脉冲、暂态振荡、电压凹陷与电压骤升等电能质量暂态扰动信号,并将扰动进行自动类型识别。通过对小波理论的研究以及数据测试实践,该方法在实际应用中取得了良好的效果。
目前,国内外都在谐波源辨识方面的研究,希望发展一种适用更广泛的可靠的谐波源定位方法,来解决现有的电能质量责任判定问题。本论文开展了这方面的探讨。论文分析了电力系统中的谐波源对电网的影响,研究了不同性质的负载与谐波的关系。列举了几种现在正在研究中的识别谐波源的技术原理,着重研究了当前电力系统中应用最广泛的谐波潮流计算和谐波功率流向法的应用,推导了谐波功率流向法的在不用网络参数下的适用性,总结了影响功率流向法适用范围和可靠性的相关因素。
Power Quality (PQ) research is an important leading edge in the powersystem. By the development of modem technology, factors of power qualityproblems are increased. For example, using non-linear loads such as powerelectric devices, and start and stop of large electric equipment load to a resultthat the problems become much more serious. For some reasons, China isespecially lagging behind in reliability and stability of power system voltageindex. Therefore, how to enhance and ensure power quality is becoming animperious task in the field of the world electrical area.
In present thesis, the classification and feature description of the most ofdisturbance waveforms are introduced and analyzed. One of the mostimportant issues in PQ problems is how to detect and classify disturbancewaveforms automatically in an efficient manner, which is the basis of PQtransient disturbance monitoring arithmetic and auto-classification. Dyadicwavelet transform, multi-resolution analysis and power mutation analysis areused to investigate kinds of transient power quality disturbance signal. Amethod is designed based on dyadic wavelet transform, which is to examinepower quality signal such as impulsive, oscillatory, sag, swell and notchwaveforms and auto-classify these kinds of disturbances. Through theacademic resource and data test, this method proves a good result in practice.
Presently, technology research is doing all over the world to develop aproved method which is more reliable in abroad areas for harmonic sourcelocation to solve the problem of power quality responsibility determination.In this paper, these problems are discussed. Influence of power system byharmonic source and loads of different characteristics are discussed in thepaper. Some technology theories on harmonic source recognition areparticularized especially the application of harmonic flow calculation andharmonic power direction method. The applicability of harmonic power
direction method under different system parameters is derived and thecorrelated aspects that affect the reliability and application condition ofharmonic power direction are summarized.
本论文对电能质量问题的分类以及各类电能质量问题的特征进行了综述。论文采用二进正交小波变换的方法、多分辨分析方法以及功率突变法等分析方法对各类短时电能质量扰动信号进行分析,设计出一种基于二进小波分析的计算方法,用于检测暂态脉冲、暂态振荡、电压凹陷与电压骤升等电能质量暂态扰动信号,并将扰动进行自动类型识别。通过对小波理论的研究以及数据测试实践,该方法在实际应用中取得了良好的效果。
目前,国内外都在谐波源辨识方面的研究,希望发展一种适用更广泛的可靠的谐波源定位方法,来解决现有的电能质量责任判定问题。本论文开展了这方面的探讨。论文分析了电力系统中的谐波源对电网的影响,研究了不同性质的负载与谐波的关系。列举了几种现在正在研究中的识别谐波源的技术原理,着重研究了当前电力系统中应用最广泛的谐波潮流计算和谐波功率流向法的应用,推导了谐波功率流向法的在不用网络参数下的适用性,总结了影响功率流向法适用范围和可靠性的相关因素。
Power Quality (PQ) research is an important leading edge in the powersystem. By the development of modem technology, factors of power qualityproblems are increased. For example, using non-linear loads such as powerelectric devices, and start and stop of large electric equipment load to a resultthat the problems become much more serious. For some reasons, China isespecially lagging behind in reliability and stability of power system voltageindex. Therefore, how to enhance and ensure power quality is becoming animperious task in the field of the world electrical area.
In present thesis, the classification and feature description of the most ofdisturbance waveforms are introduced and analyzed. One of the mostimportant issues in PQ problems is how to detect and classify disturbancewaveforms automatically in an efficient manner, which is the basis of PQtransient disturbance monitoring arithmetic and auto-classification. Dyadicwavelet transform, multi-resolution analysis and power mutation analysis areused to investigate kinds of transient power quality disturbance signal. Amethod is designed based on dyadic wavelet transform, which is to examinepower quality signal such as impulsive, oscillatory, sag, swell and notchwaveforms and auto-classify these kinds of disturbances. Through theacademic resource and data test, this method proves a good result in practice.
Presently, technology research is doing all over the world to develop aproved method which is more reliable in abroad areas for harmonic sourcelocation to solve the problem of power quality responsibility determination.In this paper, these problems are discussed. Influence of power system byharmonic source and loads of different characteristics are discussed in thepaper. Some technology theories on harmonic source recognition areparticularized especially the application of harmonic flow calculation andharmonic power direction method. The applicability of harmonic power
direction method under different system parameters is derived and thecorrelated aspects that affect the reliability and application condition ofharmonic power direction are summarized.
引文
[1] 马维新. 电力系统电压. 北京:中国电力出版社, 1998.
[2] 蔡邠. 电力系统频率. 北京:中国电力出版社, 1998
[3] 吕润馀. 电力系统高次谐波. 北京:中国电力出版社, 1998
[4] 孙树勤. 电压波动与闪变. 北京:中国电力出版社, 1998
[5] 林海雪. 电力系统的三相不平衡. 北京:中国电力出版社, 1998
[6] IEEE Std 929-2000. IEEE Recommended Practice for Utility Interface of Photovoltaic (PV) Systems. IEEE-SA Standards Board. IEEE Standards Coordinating Committee 21 on Fuel Cells, Photovoltaics, Dispersed Generation, and Energy Storage. 30 January 2000
[7] 1547~(TM)-2003. IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems. The Institute of Electrical and Electronics Engineers, Inc. 3 Park Avenue, New York, NY 10016-5997, USA. 28 July 2003
[8] I. N. Sneddon 著,I. N. Sneddon Zhu,何衍璇,张燮译. 富利叶变换. 北京:科学出版社,1958
[9] Sanatowo S,Powers E J,Grady W M. Power Quality Disturbance Identification Using Wavelet Transforms and Artifician Neural Networks. Proceeding of IEEE ICHQP VI,Las Vegas(USA),1996,615~618
[10] Perunicic B,Mallini M,Wang Z,et al. Power Quality Disturbance Detection and Classification Using Wavelet Transforms and Artifician Neural Networks. Proceeding of IEEE ICHQP VIII,Athens(Greece),1998,77~82
[11] Heydt G T,Galli A W. Transient Power Quality Problems Analyzed Using Wavelets. IEEE Trans on Power Delivery,1997,12(2):908~915
[12] Gonen,Turan. Electric power distribution system engineering. New York: McGraw-Hill Book,1986,37~90
[13] Wallach,Y. Calculations and programs for power system networks. USA: Englewood Cliffs, N.J,1986,351~375
[14] Arrillaga,J. Power system harmonics. New Zealand: Chichester [West Sussex],1985,110~197
[15] Jiansheng Huang, Michael Negnevitsky. A neural-fuzzy classifier for recognition of power quality disturbances. IEEE Transactions on Power system delivery,2002,17(2):609~616
[16] T. X. Zhu,S.K.Tso,K.L.Lo. Wavelet-based fuzzy reasoning approach to power-quality disturbance recognition. IEEE Transactions on Power system delivery,2004,19(4): 1928~1935
[17] Zwe-Lee Gaing. Wavelet-based neural network for power disturbance recognition and classification. IEEE Transactions on Power system delivery,2004,19(4):1560~1568
[18] 李世雄. 小波变换及其应用.北京:高等教育出版社,1997
[19] Chul Hwan Kim,Raj Aggarwal. Wavelet transforms in power systems. Power engineering journal,August 2001:193~202
[20] 冉启文. 小波变换与分数傅里叶变换理论及应用. 哈尔滨:哈尔滨工业大学出版社,2001
[21] Kolaczyk, E.D. Wavelet Methods for the Inversion of Certain Homogeneous Linear Operators in the Presence of Noisy Data. Ph.D. Thesis, Department of Statistics, Stanford University.,1994
[22] 胡国胜,任震,黄雯莹. 小波变换在电力系统中应用研究. 电力自动化设备,2002,22(3):71~78
[23] 李友军等. 连续小波变换应用于电力系统行波奇异性检测的探讨. 电力系统自动化,2002,26(12):54~58
[24] 钱苏翔. 傅里叶变换及小波变换的工程应用. 嘉兴高等专科学校学报,2000,13(2):39~41
[25] 陈祥训. 采用小波技术的几种电能质量扰动的测量与分类方法. 中国电机工程学报,2002,22(10):1~6
[26] 徐永海. 小波变换在电能质量分析中的应用. 电力系统自动化,1999. 23(23):55~58
[27] Wilsun Xu. An investigation on the validity of power-direction method for harmonic source determination. IEEE Transactions on Power system delivery,2003,18(1):214~219
[28] 陈永海,肖湘宁. 小波变换在电能质量分析中的应用. 电力系统自动化,1999,23(23):55~58
[29] Hossein Mokhtari,Masoud Karimi-Ghartemani。M.Reza Iravani. Experimental performance evaluation of a wavelet-based on-line voltage detection method for power quality applications. IEEE Transactions on Power system delivery,2002,17(1):161~172
[30] Z.-P.Du,J.Arrillaga,N.Watson. Continuous harmonic state estimation of power systems. IEE Proc.-Gener Transm Distrib,1996,143(4):329~336
[31] haili Ma. Identification and tracking of harmonic sources in a power system using a Kalman filter. IEEE Transactions on Power Delivery,1996,11(3):1659~1665
[32] N.R.Watson. Modified symbolic observability for harmonic state estimation. IEE Proc.-Gener Transm Distrib,2000,147(2):105~111
[33] J.E.Farach. Optimal harmonic sensor placement in fundamental network topologies. IEE Proc.-Gener Transm Distrib,1996,143(6):608~612
[34] 宋文南. 电力系统潮流计算. 天津: 天津大学出版社,1990
[35] 许克明. 电力系统高次谐波. 重庆: 重庆大学出版社,1991
[36] 宋文南,刘宝仁. 电力系统谐波分析. 北京: 水利电力出版社,1995
[37] 吴竞昌. 电力系统谐波. 北京:水利电力出版社,1988.
[38] (新西兰) 阿里拉加,唐统一. 电力系统谐波. 徐州:中国矿业大学出版社, 1991
[39] 张一中. 电力谐波. 成都:成都科技大学出版社,1992
[40] A.Cavallini,M.Cacciari,M.Loggini. Evaluation of harmonic levels in electrical networks by statistical indexes. IEEE Transactions on Industry Applications,1994,30(4):1116~1126
[41] Chun Li,Wilsun Xu. A critical impedance-based method for identifying harmonic sources. IEEE Transactions on Power system delivery,2004,19(2):671~678
[42] Wilsun Xu,Yilu Liu. A method for determining customer and utility harmonic contributions at the point of common coupling. IEEE Transactions on Power system delivery,2000,15(2):804~811
[43] Chun Li, Wilsun Xu. On defining harmonic contributions at the point of common coupling. IEEE Power Engineering Review,2002,6:44~45
[44] Hartana R K, Richards R G. Harmonic source monitoring and Identification using neural networks [J ]. IEEE Transactions on Power system,1990,5 (4) : 1098 -1104
[2] 蔡邠. 电力系统频率. 北京:中国电力出版社, 1998
[3] 吕润馀. 电力系统高次谐波. 北京:中国电力出版社, 1998
[4] 孙树勤. 电压波动与闪变. 北京:中国电力出版社, 1998
[5] 林海雪. 电力系统的三相不平衡. 北京:中国电力出版社, 1998
[6] IEEE Std 929-2000. IEEE Recommended Practice for Utility Interface of Photovoltaic (PV) Systems. IEEE-SA Standards Board. IEEE Standards Coordinating Committee 21 on Fuel Cells, Photovoltaics, Dispersed Generation, and Energy Storage. 30 January 2000
[7] 1547~(TM)-2003. IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems. The Institute of Electrical and Electronics Engineers, Inc. 3 Park Avenue, New York, NY 10016-5997, USA. 28 July 2003
[8] I. N. Sneddon 著,I. N. Sneddon Zhu,何衍璇,张燮译. 富利叶变换. 北京:科学出版社,1958
[9] Sanatowo S,Powers E J,Grady W M. Power Quality Disturbance Identification Using Wavelet Transforms and Artifician Neural Networks. Proceeding of IEEE ICHQP VI,Las Vegas(USA),1996,615~618
[10] Perunicic B,Mallini M,Wang Z,et al. Power Quality Disturbance Detection and Classification Using Wavelet Transforms and Artifician Neural Networks. Proceeding of IEEE ICHQP VIII,Athens(Greece),1998,77~82
[11] Heydt G T,Galli A W. Transient Power Quality Problems Analyzed Using Wavelets. IEEE Trans on Power Delivery,1997,12(2):908~915
[12] Gonen,Turan. Electric power distribution system engineering. New York: McGraw-Hill Book,1986,37~90
[13] Wallach,Y. Calculations and programs for power system networks. USA: Englewood Cliffs, N.J,1986,351~375
[14] Arrillaga,J. Power system harmonics. New Zealand: Chichester [West Sussex],1985,110~197
[15] Jiansheng Huang, Michael Negnevitsky. A neural-fuzzy classifier for recognition of power quality disturbances. IEEE Transactions on Power system delivery,2002,17(2):609~616
[16] T. X. Zhu,S.K.Tso,K.L.Lo. Wavelet-based fuzzy reasoning approach to power-quality disturbance recognition. IEEE Transactions on Power system delivery,2004,19(4): 1928~1935
[17] Zwe-Lee Gaing. Wavelet-based neural network for power disturbance recognition and classification. IEEE Transactions on Power system delivery,2004,19(4):1560~1568
[18] 李世雄. 小波变换及其应用.北京:高等教育出版社,1997
[19] Chul Hwan Kim,Raj Aggarwal. Wavelet transforms in power systems. Power engineering journal,August 2001:193~202
[20] 冉启文. 小波变换与分数傅里叶变换理论及应用. 哈尔滨:哈尔滨工业大学出版社,2001
[21] Kolaczyk, E.D. Wavelet Methods for the Inversion of Certain Homogeneous Linear Operators in the Presence of Noisy Data. Ph.D. Thesis, Department of Statistics, Stanford University.,1994
[22] 胡国胜,任震,黄雯莹. 小波变换在电力系统中应用研究. 电力自动化设备,2002,22(3):71~78
[23] 李友军等. 连续小波变换应用于电力系统行波奇异性检测的探讨. 电力系统自动化,2002,26(12):54~58
[24] 钱苏翔. 傅里叶变换及小波变换的工程应用. 嘉兴高等专科学校学报,2000,13(2):39~41
[25] 陈祥训. 采用小波技术的几种电能质量扰动的测量与分类方法. 中国电机工程学报,2002,22(10):1~6
[26] 徐永海. 小波变换在电能质量分析中的应用. 电力系统自动化,1999. 23(23):55~58
[27] Wilsun Xu. An investigation on the validity of power-direction method for harmonic source determination. IEEE Transactions on Power system delivery,2003,18(1):214~219
[28] 陈永海,肖湘宁. 小波变换在电能质量分析中的应用. 电力系统自动化,1999,23(23):55~58
[29] Hossein Mokhtari,Masoud Karimi-Ghartemani。M.Reza Iravani. Experimental performance evaluation of a wavelet-based on-line voltage detection method for power quality applications. IEEE Transactions on Power system delivery,2002,17(1):161~172
[30] Z.-P.Du,J.Arrillaga,N.Watson. Continuous harmonic state estimation of power systems. IEE Proc.-Gener Transm Distrib,1996,143(4):329~336
[31] haili Ma. Identification and tracking of harmonic sources in a power system using a Kalman filter. IEEE Transactions on Power Delivery,1996,11(3):1659~1665
[32] N.R.Watson. Modified symbolic observability for harmonic state estimation. IEE Proc.-Gener Transm Distrib,2000,147(2):105~111
[33] J.E.Farach. Optimal harmonic sensor placement in fundamental network topologies. IEE Proc.-Gener Transm Distrib,1996,143(6):608~612
[34] 宋文南. 电力系统潮流计算. 天津: 天津大学出版社,1990
[35] 许克明. 电力系统高次谐波. 重庆: 重庆大学出版社,1991
[36] 宋文南,刘宝仁. 电力系统谐波分析. 北京: 水利电力出版社,1995
[37] 吴竞昌. 电力系统谐波. 北京:水利电力出版社,1988.
[38] (新西兰) 阿里拉加,唐统一. 电力系统谐波. 徐州:中国矿业大学出版社, 1991
[39] 张一中. 电力谐波. 成都:成都科技大学出版社,1992
[40] A.Cavallini,M.Cacciari,M.Loggini. Evaluation of harmonic levels in electrical networks by statistical indexes. IEEE Transactions on Industry Applications,1994,30(4):1116~1126
[41] Chun Li,Wilsun Xu. A critical impedance-based method for identifying harmonic sources. IEEE Transactions on Power system delivery,2004,19(2):671~678
[42] Wilsun Xu,Yilu Liu. A method for determining customer and utility harmonic contributions at the point of common coupling. IEEE Transactions on Power system delivery,2000,15(2):804~811
[43] Chun Li, Wilsun Xu. On defining harmonic contributions at the point of common coupling. IEEE Power Engineering Review,2002,6:44~45
[44] Hartana R K, Richards R G. Harmonic source monitoring and Identification using neural networks [J ]. IEEE Transactions on Power system,1990,5 (4) : 1098 -1104