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Method of Detection Optimization Based on Vector Electric Field Multi-electrode Gradient Information

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Proceedings of 2017 Chinese Intelligent Automation Conference (CIAC 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 458))

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Abstract

This paper presents a method that the algorithm of calculating the electric field combining with vector electric field multi-electrode gradient information is optimized by using the compression-aware greedy reconstruction algorithm, which can effectively identify the electric field gradient information and improve the accuracy rate of the voltage level detection judgment, through the research on the calculation method of the electric field gradient information of the electrical equipment in the substation. This method can accurately calculate the electric field distribution and voltage level around the high voltage conductor by analyzing the electric field information around the charged body. The distribution of the field strength at one interval of the charged carrier is obtained by tested in complex power frequency electric field environment of the 110 kV substation equipment. The results show that the method can effectively improve the detection capability of the voltage level of the charged carrier and the response speed of the electric field around the charged body, and improve the safety of the staff working in the complex electric field.

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Acknowledgements

State Grid Corporation of Science and Technology Project (526816160024).

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Correspondence to Jianjun Liu .

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Liu, J. et al. (2018). Method of Detection Optimization Based on Vector Electric Field Multi-electrode Gradient Information. In: Deng, Z. (eds) Proceedings of 2017 Chinese Intelligent Automation Conference. CIAC 2017. Lecture Notes in Electrical Engineering, vol 458. Springer, Singapore. https://doi.org/10.1007/978-981-10-6445-6_4

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  • DOI: https://doi.org/10.1007/978-981-10-6445-6_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6444-9

  • Online ISBN: 978-981-10-6445-6

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