Abstract
During the operation of the power network, there was a sharp change in current and voltage at the time of failure, which made it difficult for the grid operators to quickly and accurately determine the fault. This paper proposed a big data-based power network fault feature analysis method design. Taking the symmetrical fault component method as the main analysis method, a two-phase short-circuit equivalent model was constructed by accurately analyzing the fault characteristics of the power network, and the fault features were detected and located by the big data network preprocessor. The experimental results shown that the big data power network fault feature analysis method could effectively feedback and locate the fault location and complete the maintenance of the power network in time.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Di, Cy. (2019). Fault Feature Analysis of Power Network Based on Big Data. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_15
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DOI: https://doi.org/10.1007/978-3-030-36402-1_15
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