基于小波变换的波浪发电输电电缆绝缘监测
|
摘要
针对波浪发电孤岛供电系统中电力电缆在海洋环境下容易出现绝缘故障问题,为实现其绝缘状态的实时监测,采用基于局部放电信号的绝缘监测算法,建立电缆和局部放电信号的数学和仿真模型.通过小波变换和Sqtwolog阈值策略完成局部放电信号的去噪重构,最后提取其特征量对输电电缆绝缘状态进行在线监测.高压现场实验数据表明,3种不同电缆绝缘破坏程度的局部放电量分别为16.7,34.2和46.5 pC,放电量增长趋势与实验情况相符,从而验证了此绝缘监测算法的实用性和可行性.
The power cable in the wave power generation of an island power supply system is prone to have insulation faults in the marine environment. To realize real-time monitoring of its insulation state, a partial discharge method was used to monitor the cable, and the mathematical models of the cable and partial discharge wave were established. The wavelet transform and the Sqtwolog threshold strategy were used to denoise and reconstruct the partial discharge signals. And the cable insulation state was achieved by extracting signal features. Finally, the high-voltage experiments with three different insulation failures were conducted in practical situation. The experimental results show that the partial discharges are 16.7, 34.2 and 46.5 pC, respectively. The discharge trend is consistent with the experimental conditions. Thus, it verifies the reliability and the effectiveness of the insulation monitoring method.
The power cable in the wave power generation of an island power supply system is prone to have insulation faults in the marine environment. To realize real-time monitoring of its insulation state, a partial discharge method was used to monitor the cable, and the mathematical models of the cable and partial discharge wave were established. The wavelet transform and the Sqtwolog threshold strategy were used to denoise and reconstruct the partial discharge signals. And the cable insulation state was achieved by extracting signal features. Finally, the high-voltage experiments with three different insulation failures were conducted in practical situation. The experimental results show that the partial discharges are 16.7, 34.2 and 46.5 pC, respectively. The discharge trend is consistent with the experimental conditions. Thus, it verifies the reliability and the effectiveness of the insulation monitoring method.
引文
[1] Falc?o A F de O. Wave energy utilization: A review of the technologies[J]. Renewable and Sustainable Energy Reviews, 2010, 14(3): 899-918. DOI:10.1016/j.rser.2009.11.003.
[2] Liu C Y, Yu H T, Liu Q, et al. Research on a double float system for direct drive wave power conversion[J]. IET Renewable Power Generation, 2017, 11(7): 1026-1032. DOI:10.1049/iet-rpg.2016.0620.
[3] Xia T, Yu H T, Chen Z X, et al. Design and analysis of a field-modulated tubular linear permanent magnet generator for direct-drive wave energy conversion[J]. IEEE Transactions on Magnetics, 2017, 53(6): 1-4. DOI:10.1109/tmag.2017.2662080.
[4] Huang L, Yu H T, Hu M Q, et al. Research on a tubular primary permanent-magnet linear generator for wave energy conversions[J]. IEEE Transactions on Magnetics, 2013, 49(5): 1917-1920. DOI:10.1109/tmag.2013.2239981.
[5] 陈向荣, 徐阳, 王猛, 等. 高温下110 kV交联聚乙烯电缆电树枝生长及局部放电特性[J]. 高电压技术, 2012, 38(3): 645-654. DOI:10.3969/j.issn.1003-6520.2012.03.019.Chen X R, Xu Y, Wang M, et al. Propagation and partial discharge characteristics of electrical trees in 110 kV XLPE cable insulation at high temperature[J]. High Voltage Engineering, 2012, 38(3): 645-654. DOI:10.3969/j.issn.1003-6520.2012.03.019. (in Chinese)
[6] Zhu B, Wei X L, Pang B, et al. Study on on-line insulation monitoring for 500 kV submarine cable[C]//2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA). Ottawa, ON, Canada, 2014: 1171-1174. DOI:10.1109/WARTIA.2014.6976488.
[7] Lü A, Li J. On-line monitoring system of 35 kV 3-core submarine power cable based on φ-OTDR[J]. Sensors and Actuators A: Physical, 2018, 273: 134-139. DOI:10.1016/j.sna.2018.02.033.
[8] 蒋奇, 张建, 杨黎鹏. 海底高压动力电缆在线监测技术与实验研究[J]. 高电压技术, 2007, 33(8): 198-202. DOI:10.3969/j.issn.1003-6520.2007.08.046.Jiang Q, Zhang J, Yang L P. Experimental study on monitoring of high voltage power cable in seabed[J].High Voltage Engineering, 2007, 33(8): 198-202. DOI:10.3969/j.issn.1003-6520.2007.08.046.(in Chinese)
[9] 汪洋, 李捍平, 林晓波, 等. 基于分布式光纤振动传感的海底电缆绝缘击穿故障检测[J]. 电线电缆, 2018(1): 31-34. DOI:10.16105/j.cnki.dxdl.2018.01.009.Wang Y, Li H P, Lin X B, et al. Detection of submarine power cable insulation breakdown based on distributed optical fiber vibration sensor[J].Wire & Cable, 2018(1): 31-34. DOI:10.16105/j.cnki.dxdl.2018.01.009.(in Chinese)
[10] Wang H, Zhang L, Huang C J, et al. Intelligent morphological filter applied to the signal processing of partial discharge for XLPE cable[C]//2009 IEEE International Conference on Intelligent Computing and Intelligent Systems. Shanghai, China, 2009: 708-712. DOI:10.1109/ICICISYS.2009.5358397.
[11] Ashtiani M, Shahrtash S. Partial discharge de-noising employing adaptive singular value decomposition[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2014, 21(2): 775-782. DOI:10.1109/tdei.2013.003894.
[12] Jayakrishnan M, Rao B N. Application of modified wavelet packet transform for de-noising during partial discharge measurement on power cables[C]//2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON). Rupnagar, India, 2017: 253-258. DOI:10.1109/CATCON.2017.8280223.
[13] Mitchell S D, Welsh J S, Middleton R H, et al. A narrowband high frequency distributed power transformer model for partial discharge location[C]//2007 Australasian Universities Power Engineering Conference. Perth, WA, Australia, 2007: 1-7. DOI:10.1109/AUPEC.2007.4548109.
[14] 唐炬, 李伟, 欧阳有鹏. 采用小波变换奇异值分解方法的局部放电模式识别[J]. 高电压技术, 2010, 36(7): 1686-1691. DOI:10.13336/j.1003-6520.hve.2010.07.031.Tang J, Li W, Ouyang Y P. Partial discharge pattern recognition using discrete wavelet transform and singular value decomposition[J].High Voltage Engineering, 2010, 36(7): 1686-1691. DOI:10.13336/j.1003-6520.hve.2010.07.031. (in Chinese)
[2] Liu C Y, Yu H T, Liu Q, et al. Research on a double float system for direct drive wave power conversion[J]. IET Renewable Power Generation, 2017, 11(7): 1026-1032. DOI:10.1049/iet-rpg.2016.0620.
[3] Xia T, Yu H T, Chen Z X, et al. Design and analysis of a field-modulated tubular linear permanent magnet generator for direct-drive wave energy conversion[J]. IEEE Transactions on Magnetics, 2017, 53(6): 1-4. DOI:10.1109/tmag.2017.2662080.
[4] Huang L, Yu H T, Hu M Q, et al. Research on a tubular primary permanent-magnet linear generator for wave energy conversions[J]. IEEE Transactions on Magnetics, 2013, 49(5): 1917-1920. DOI:10.1109/tmag.2013.2239981.
[5] 陈向荣, 徐阳, 王猛, 等. 高温下110 kV交联聚乙烯电缆电树枝生长及局部放电特性[J]. 高电压技术, 2012, 38(3): 645-654. DOI:10.3969/j.issn.1003-6520.2012.03.019.Chen X R, Xu Y, Wang M, et al. Propagation and partial discharge characteristics of electrical trees in 110 kV XLPE cable insulation at high temperature[J]. High Voltage Engineering, 2012, 38(3): 645-654. DOI:10.3969/j.issn.1003-6520.2012.03.019. (in Chinese)
[6] Zhu B, Wei X L, Pang B, et al. Study on on-line insulation monitoring for 500 kV submarine cable[C]//2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA). Ottawa, ON, Canada, 2014: 1171-1174. DOI:10.1109/WARTIA.2014.6976488.
[7] Lü A, Li J. On-line monitoring system of 35 kV 3-core submarine power cable based on φ-OTDR[J]. Sensors and Actuators A: Physical, 2018, 273: 134-139. DOI:10.1016/j.sna.2018.02.033.
[8] 蒋奇, 张建, 杨黎鹏. 海底高压动力电缆在线监测技术与实验研究[J]. 高电压技术, 2007, 33(8): 198-202. DOI:10.3969/j.issn.1003-6520.2007.08.046.Jiang Q, Zhang J, Yang L P. Experimental study on monitoring of high voltage power cable in seabed[J].High Voltage Engineering, 2007, 33(8): 198-202. DOI:10.3969/j.issn.1003-6520.2007.08.046.(in Chinese)
[9] 汪洋, 李捍平, 林晓波, 等. 基于分布式光纤振动传感的海底电缆绝缘击穿故障检测[J]. 电线电缆, 2018(1): 31-34. DOI:10.16105/j.cnki.dxdl.2018.01.009.Wang Y, Li H P, Lin X B, et al. Detection of submarine power cable insulation breakdown based on distributed optical fiber vibration sensor[J].Wire & Cable, 2018(1): 31-34. DOI:10.16105/j.cnki.dxdl.2018.01.009.(in Chinese)
[10] Wang H, Zhang L, Huang C J, et al. Intelligent morphological filter applied to the signal processing of partial discharge for XLPE cable[C]//2009 IEEE International Conference on Intelligent Computing and Intelligent Systems. Shanghai, China, 2009: 708-712. DOI:10.1109/ICICISYS.2009.5358397.
[11] Ashtiani M, Shahrtash S. Partial discharge de-noising employing adaptive singular value decomposition[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2014, 21(2): 775-782. DOI:10.1109/tdei.2013.003894.
[12] Jayakrishnan M, Rao B N. Application of modified wavelet packet transform for de-noising during partial discharge measurement on power cables[C]//2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON). Rupnagar, India, 2017: 253-258. DOI:10.1109/CATCON.2017.8280223.
[13] Mitchell S D, Welsh J S, Middleton R H, et al. A narrowband high frequency distributed power transformer model for partial discharge location[C]//2007 Australasian Universities Power Engineering Conference. Perth, WA, Australia, 2007: 1-7. DOI:10.1109/AUPEC.2007.4548109.
[14] 唐炬, 李伟, 欧阳有鹏. 采用小波变换奇异值分解方法的局部放电模式识别[J]. 高电压技术, 2010, 36(7): 1686-1691. DOI:10.13336/j.1003-6520.hve.2010.07.031.Tang J, Li W, Ouyang Y P. Partial discharge pattern recognition using discrete wavelet transform and singular value decomposition[J].High Voltage Engineering, 2010, 36(7): 1686-1691. DOI:10.13336/j.1003-6520.hve.2010.07.031. (in Chinese)