全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

电压暂降状态和水平评估模式匹配法与监测装置多目标优化配置

DOI: 10.13334/j.0258-8013.pcsee.2015.13.009, PP. 3264-3271

Keywords: 模式匹配,暂降状态,暂降水平,监测冗余度,优化配置,多目标优化

Full-Text   Cite this paper   Add to My Lib

Abstract:

为准确评估电网电压暂降状态和暂降水平,引入电压暂降模式相关概念。基于电网故障模式与由其引起的暂降模式之间的关系,用模式匹配方法、监测数据和仿真方法,确定最匹配暂降模式,并由此进行电网暂降状态和水平估计。为优化监测装置的配置,充分利用监测冗余信息,同时考虑监测装置数量最少和监测冗余度最大,提出满足全网暂降状态可观的多目标优化模型。仅需按0.9pu暂降阈值进行监测装置配置,就能准确评估全网暂降状态和水平,所需监测装置数量少、监测装置的配置方案唯一,电网暂降状态和水平估计精度高。对IEEE30节点系统进行仿真,证明了所提方法的正确性和有效性。该方法还具有原理简单、寻优方便等特点。

References

[1]  Mokhlis H,Mohamad H,Li H Y,et al.Voltage sags matching to locate faults for underground distribution networks[J].Advances in Electrical and Computer Engineering,2011,11(2):43-48.
[2]  Rahm E,Bernstein P A.A survey of approaches to automatic schema matching[J].The International Journal on Very Large Data Bases,2001,10(4):334-350.
[3]  张治,车皓阳,施鹏飞.模式匹配问题的描述框架与算法模型[J].模式识别与人工智能,2006,19(6):715-721.Zhang Zhi,Che Haoyang,Shi Pengfei.Framework and algorithm model of schema matching problem[J].Pattern Recognition and Artificial Intelligence,2006,19(6):715-721(in Chinese).
[4]  IEEE Standard 1159-1995.IEEE recommended practice for monitoring electric power quality[S].New York:IEEE Press,1995.
[5]  杜雄,周雒维,许可夫.基于双dq变换的引起电压暂降的短路故障分类[J].电力系统自动化,2010,34(5):86-90.Du Xiong,Zhou Luowei,Xu Kefu.Classification of short circuit faults causing voltage sags based on double dq transformation[J].Automation of Electric Power Systems,2010,34(5):86-90(in Chinese).
[6]  Liao Y.Fault location for single-circuit line based on bus-impedance matrix utilizing voltage measurements [J].IEEE Transactions on Power Delivery,2008,23(2):609-617.
[7]  傅英定,成孝予,唐应辉.最优化理论与方法[M].北京:国防工业出版社,2008:313-329.Fu Yingding,Cheng Xiaoyu,Tang Yinghui.Optimization theory and method[M].Beijing:National Defence Industry Press,2008:313-329(in Chinese).
[8]  黄红选,韩继业.数学规划[M].北京:清华大学出版社,2006:381-387.Huang Hongxuan,Han Jiye.Mathematical programming [M].Beijing:Tsinghua University Press,2006:381-387(in Chinese).
[9]  University of Washington electrical engineering.30 bus power flow test case[EB/OL].1993-08-15[2014-08-.http//www.ee.washington.edu/research/pstca/pf30/pg_tca30bus.htm.
[10]  陶顺,肖湘宁,刘晓娟.电压暂降对配电系统可靠性影响及其评估指标的研究[J].中国电机工程学报,2005,25(21):63-69.Tao Shun,Xiao Xiangning,Liu Xiaojuan.Study on distribution reliability considering voltage sags and acceptable indices[J].Proceedings of the CSEE,2005,25(21):63-69(in Chinese).
[11]  刘旭娜,肖先勇,汪颖.电压暂降严重程度及其测度、不确定性评估方法[J].中国电机工程学报,2014,34(4):644-658.Liu Xuna,Xiao Xianyong,Wang Ying.Voltage sag severity and its measure and uncertainty evaluation [J].Proceedings of the CSEE,2014,34(4):644-658 (in Chinese).
[12]  Qader R Q,Bollen M H J,Allan R N.Stochastic prediction of voltage sags in a large transmission system [J].IEEE Transactions on Industry Applications,1999,35(1):152-162.
[13]  Park C H,Jang G.Stochastic estimation of voltage sags in a large meshed network[J].IEEE Transactions on Power Delivery,2007,22(3):1655-1664.
[14]  肖先勇,陈卫东,杨洪耕,等.以用户满意度区间数为测度的电压暂降频次评估[J].中国电机工程学报,2010,30(16):104-110.Xiao Xianyong,Chen Weidong,Yang Honggeng,et al.Voltage sag frequency assessment under the measure of interval data of customer satisfaction[J].Proceedings of the CSEE,2010,30(16):104-110(in Chinese).
[15]  杨晓东,李庚银,周明,等.电压暂降随机预估的自适应信赖域方法[J].中国电机工程学报,2011,31(4):39-44.Yang Xiaodong,Li Gengyin,Zhou Ming,et al.Adaptive trust region method for stochastic estimation of voltage sags[J].Proceedings of the CSEE,2011,31(4):39-44(in Chinese).
[16]  Espinosa-Juarez E,Hernandez A.A method for voltage sags state estimation in power systems[J].IEEE Transactions on Power Delivery,2007,22(4):2517-2526.
[17]  Lucio J,Espinosa-Juarez E,Hernandez A.Voltage sag state estimation in power systems by applying genetic algorithms[J].IET Generation,Transmission & Distribution,2011,5(2):223-230.
[18]  Espinosa-Juarez E,Espinoza-Tinoco J R,Hernandez A.Neural networks applied to solve the voltage sag state estimation problem:an approach based on the fault positions concept[C]//2009 Electronics Robotics and Automotive Mechanics Conference.Cuernavaca,Mexico, 2009:88-93.
[19]  Hernandez A,Espinosa-Juarez E,de Castro R M,et al.SVD applied to voltage sag state estimation[J].IEEE Transactions on Power Delivery,2012,28(2):866-874.
[20]  齐林海,艾明浩.一种基于云计算的电压暂降并行计算方法[J].中国电机工程学报,2014,34(31):5493-5499.Qi Linhai,Ai Minghao.A voltage sag parallel calculation method based on cloud computing[J].Proceedings of the CSEE,2014,34(31):5493-5499(in Chinese).
[21]  Milanovic J V,Aung M T,Gupta C P,The influence of fault distribution on stochastic prediction of voltage sags [J].IEEE Transactions on Power Delivery,2005,20(1):278-285.
[22]  Olguin G,Vuinovich F,Bollen M H J.An optimal monitoring program for obtaining voltage sag system indexes[J].IEEE Transactions on Power Delivery,2006,21(1):378-384.
[23]  王东旭,乐健,刘开培,等.复杂电网多重故障条件下的电压暂降分析[J].中国电机工程学报,2012,32(7):101-106.Wang Dongxu,Le Jian,Liu Kaipei,et al.Voltage dip analysis for multiple faults case in complex power grid [J].Proceedings of the CSEE,2012,32(7):101-106(in Chinese).
[24]  刘颖英,王同勋,冯丹丹,等.基于多重判据的电压暂降故障源定位方法[J].中国电机工程学报,2015,35(1):103-111.Liu Yingying,Wang Tongxun,Feng Dandan,et al.Multiple criterions based voltage sag location method [J].Proceedings of the CSEE,2015,35(1):103-111(in Chinese).
[25]  Romero M,Gallego L,Pavas A.Fault zones location on distribution systems based on clustering of voltage sags patterns[C]//2012 IEEE 15th International Conference on Harmonics and Quality of Power.Hong Kong,China:IEEE,2012:486-493.
[26]  Mokhlis H,Khalid A R,Li H Y.Voltage sags pattern recognition technique for fault section identification in distribution networks[C]//2009 IEEE Bucharest Power Technology.Bucharest,Romania:IEEE,2009:1-6.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133