李岩;滕云;苑舜;冷欧阳;

• 1:沈阳工业大学电气工程学院
• 2:国网内蒙古东部电力有限公司
• 3:国网内蒙古东部电力有限公司经济技术研究院

摘要(Abstract)：

准确评估绝缘子覆雪融雪过程中闪络电压特性,对恶劣气象条件下电网安全运行水平评估和线路检修策略决策具有重要意义。针对FXBW-35/70型复合绝缘子,采用人工覆雪闪络电压试验方法,对均匀覆雪和不均匀覆雪绝缘子串的覆雪期、融雪初期和融雪后期3个阶段的闪络电压特性进行了试验研究,分析了各阶段闪络电压和泄漏电流变化特征及其产生原因。通过分析覆雪绝缘子的电场分布,探究了融雪期闪络电压变化的原因。研究基于深度自编码网络与量子神经网络结合的覆雪闪络电压特性变化建模方法,建立基于改进量子神经网络的覆雪闪络电压预测模型。人工覆雪闪络电压试验测试和验证结果表明,提出的改进量子神经网络闪络电压预测模型与单一的反向传播神经网络、支持向量机模型和遗传算法模型相比,能够更加准确地反映北方地区线路绝缘子覆雪融雪过程中的闪络电压变化特性,其预测结果可为电网安全评估与检修决策提供有效指导。

关键词(KeyWords)： 覆雪绝缘子;闪络特性;改进量子神经网络

Abstract:

Keywords:

基金项目(Foundation): 沈阳市科技计划项目(Y17-0-007)~~

作者(Author): 李岩;滕云;苑舜;冷欧阳;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.0599

参考文献(References)：

• [1]孙才新,舒立春,蒋兴良,等.高海拔、污秽、覆冰环境下超高压线路绝缘子交直流放电特性及闪络电压校正研究[J].中国电机工程学报,2002,22(11):116-121.Sun Caixin,Shu Lichun,Jiang Xingliang,et al.AC/DC flashover performance and its voltage correction of UHV insulators in high altitude and icing and pollution environments[J].Proceedings of the CSEE,2002,22(11):116-121(in Chinese).
• [2]向泽,蒋兴良,张志劲,等.玻璃绝缘子串自然覆冰(雪)交流闪络特性[J].高电压技术,2014,40(5):1345-1350.Xiang Ze,Jiang Xingliang,Zhang Zhijin,et al.AC Flashover performance of glass insulators covered with ice or snow at natural station[J].High Voltage Engineering,2014,40(5):1345-1350(in Chinese).
• [3]张志劲,蒋兴良,胡建林,等.110 k V支柱绝缘子交流覆冰(雪)电气特性[J].高电压技术,2009,35(10):2528-2534.Zhang Zhijin,Jiang Xingliang,Hu Jianlin,et al.AC electric characteristics of 110 k V post insulators covered with ice or snow[J].High Voltage Engineering,2009,35(10):2528-2534(in Chinese).
• [4]徐涛,王海明,王琳琳,等.500 k V瓷支柱绝缘子加装复合增爬裙后的覆冰闪络特性[J].高电压技术,2012,38(1):167-172.Xu Tao,Wang Haiming,Wang Linlin,et al.Flashover performance of 500 k V ice-covered porcelain post insulators with composite assistant shed[J].High Voltage Engineering,2012,38(1):167-172(in Chinese).
• [5]李隆基,郗晓光,贾志东,等.湿雪的导电性能及对其闪络特性的影响[J].绝缘材料,2017,50(11):38-43.Li Longji,Xi Xiaoguang,Jia Zhidong,et al.Conductivity of wet snow and its influence on flashover characteristics[J].Insulating Materials,2017,50(11):38-43(in Chinese).
• [6]陈吉,蒋兴良,郭钢,等.交直流电场对雨凇覆冰特性的影响研究[J].电网技术,2015,39(3):867-872.Chen Ji,Jiang Xingliang,Guo Gang,et al.Effect on the glaze icing characteristics under the AC and DC electric field[J].Power System Technology,2015,39(3):867-872(in Chinese).
• [7]胡琴,汪诗经,杨红军,等.不同伞形结构复合绝缘子覆冰增长特性研究[J].电网技术,2016,40(7):2236-2243.Hu Qin,Wang Shijing,Yang Hongjun,et al.Comparison of ice growth on composite insulators with different shed configurations[J].Power System Technology,2016,40(7):2236-2243(in Chinese).
• [8]胡琴,于洪杰,徐勋建,等.分裂导线覆冰扭转特性分析及等值覆冰厚度计算[J].电网技术,2016,40(11):3615-3944.Hu Qin,Yu Hongjie,Xu Xunjian,et al.Study on torsion characteristic and equivalent ice thickness of bundle conductors[J].Power System Technology,2016,40(11):3615-3944(in Chinese).
• [9]晏鸣宇,何宇斌,姚伟,等.基于时变结构可靠性理论的覆冰电网风险调度[J].电网技术,2017,41(6):1873-1879.Yan Mingyu,He Yubin,Yao Wei,et al.Risk-based dispatch method for icing power grid based on time-varying structural reliability theory[J].Power System Technology,2017,41(6):1873-1879(in Chinese).
• [10]李亚伟,张星海,贾志东,等.不同覆冰类型绝缘子串的泄漏电流特征分析[J].电网技术,2017,41(11):3691-3697.Li Yawei,Zhang Xinghai,Jia Zhidong,et al.Characteristic analysis of leakage current of insulator strings under different icing types[J].Power System Technology,2017,41(11):3691-3697(in Chinese).
• [11]马宁.量子神经网络及其应用研究[D].兰州:兰州理工大学,2009.
• [12]朱永利,尹金良.组合核相关向量机在电力变压器故障诊断中的应用研究[J].中国电机工程学报,2013,33(22):68-74+12.Zhu Yongli,Yin Jinliang.Study on application of multi-kernel learning relevance vector machines in fault diagnosis of power transformers[J].Proceedings of the CSEE,2013,33(22):68-74+12(in Chinese).
• [13]李胜,张培林,李兵,等.量子BP神经网络在发动机故障诊断中的应用[J].中国机械工程,2014,25(16):2159-2163.Li Sheng,Zhang Peilin,Li Bing,et al.Applications of quantum BPneural network in engine fault diagnosis[J].Mechanical Engineering,2014,25(16):2159-2163(in Chinese).
• [14]赵世华,蒋兴良,张志劲,等.染污玻璃绝缘子泄漏电流特性及其闪络电压预测[J].电网技术,2014,38(2):440-447.Zhao Shihua,Jiang Xingliang,Zhang Zhijin,et al.Flashover voltage prediction of polluted glass insulators based on the characteristics of leakage current[J].Power System Technology,2014,38(2):440-447(in Chinese).
• [15]舒立春,白困利,胡琴,等.基于支持向量机的复杂环境条件下绝缘子闪络电压的预测[J].中国电机工程学报,2006,26(17):127-131.Shu Lichun,Bai Kunli,Hu Qin,et al.Insulator flashover voltage forecasting under complex circumstance based on support vector machine[J].Proceedings of the CSEE,2006,26(17):127-131(in Chinese).
• [16]张若兵,李剑超,王黎明,等.变电站支柱绝缘子的覆雪闪络特性[J].高电压技术,2016,42(12):3823-3829.Zhang Ruobing,Li Jianchao,Wang Liming,et al.Flashover characteristics of snow-covered post insulators in substations[J].High Voltage Engineering,2016,42(12):3823-3829(in Chinese).
• [17]欧阳宝龙,连莎莎,王永强.高海拔地区冰雪共存条件下复合绝缘子沿面电场计算[J].华北电力大学学报(自然科学版),2016,43(6):54-59.Ouyang Baolong,Lian Shasha,Wang Yongqiang.Calculation on surface electric field of composite insulators under coexisting condition of ice and snow in high altitude regions[J].Journal of North China Electric Power University(Natural Science Edition),2016,43(6):54-59(in Chinese).
• [18]王永强,欧阳宝龙,连莎莎,等.高海拔地区积雪复合绝缘子沿面电场分布研究[J].高压电器,2016,52(6):115-123.Wang Yongqiang,Ouyang Baolong,Lian Shasha,et al.Study on electric field distribution along the surface of snowed composite insulator in high altitude area[J].High Voltage Apparatus,2016,52(6):115-123(in Chinese).
• [19]欧阳宝龙.积雪复合绝缘子的电气特性及选型研究[D].北京:华北电力大学,2016.
• [20]张海平,何正友,张钧.基于量子神经网络和证据融合的小电流接地选线方法[J].电工技术学报,2009,24(12):171-178.Zhang Haiping,He Zhengyou,Zhang Jun.A fault line detection method for indirectly grounding power system based on quantum neural network and evidence fusion[J].Transactions of China Electrotechnical Society,2009,24(12):171-178(in Chinese).
• [21]Narayanan A,Menneer T.Quantum artificial neural network architectures and components[J].Information Sciences,2000,128(3):231-255.
• [22]朱大奇,陈尔奎.旋转机械故障诊断的量子神经网络算法[J].中国电机工程学报,2006,26(1):132-136.Zhu Daqi,Chen Erkui.A quantum neural networks fault diagnosis algorithm for rotating machinery[J].Proceedings of the CSEE,2006,26(1):132-136(in Chinese).
• [23]Naresh R,Sharma V,Vashisth M.An integrated neural fuzzy approach for fault diagnosis of transformers[J].IEEE Transactions on Power Delivery,2008,23(4):2017-2024.
• [24]刘建伟,刘媛,罗雄麟.深度学习研究进展[J].计算机应用研究,2014,31(7):1921-1930+1942.Liu Jianwei,Liu Yuan,Luo Xionglin.Research and development on deep learning[J].Application Research of Computers,2014,31(7):1921-1930+1942(in Chinese).
• [25]黄弦超,杨雨.基于电流分点编码的遗传算法在配电网重构中的应用[J].电力系统自动化,2013,37(19):74-79.Huang Xianchao,Yang Yu.Network reconfiguration in distribution systems based on genetic algorithm[J].Automation of Electric Power Systems,2013,37(19):74-79(in Chinese).
• [26]刘超.基于粗糙集理论和量子神经网络的电网故障诊断方法研究[D].成都:西南交通大学,2008.
• [27]李盼池.一种量子神经网络模型学习算法及应用[J].控制理论与应用,2009,26(5):531-534.Li Panchi.A learning algorithm and its applications to the quantum neural network model[J].Control Theory&Applications,2009,26(5):531-534(in Chinese).