Research on electric anti-shake technology of power grid system of chemical enterprise based on process immune time

Jiaxuan Liu; Zhongjian Kang; Yisen Sun

doi:10.1117/12.2639875

19 October 2022 Research on electric anti-shake technology of power grid system of chemical enterprise based on process immune time

Jiaxuan Liu, Zhongjian Kang, Yisen Sun

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Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 1229409 (2022) https://doi.org/10.1117/12.2639875
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

Voltage sag can result in petrochemical enterprise motor running back in the process of production and process abort, lower the quality of power supply, cause huge economic losses. In view of the problem that the current voltage tolerance evaluation of petrochemical plants mainly adopts the traditional sensitive equipment tolerance curve, which cannot accurately describe the voltage sag tolerance of sensitive loads, this paper proposes a voltage sag simulation and evaluation method based on nameplate data through theoretical derivation and simulation verification. First of all to establish mathematical model of induction motor based on nameplate data to calculate the model parameters of the motor; Then, using the mechanical characteristic formula of induction motor and the mechanical characteristic formula of fan or pump load, the time of transient arrival boundary removal corresponding to voltage sag depth under different loads was deduced. Finally, a simulation model was built in Digsilent software to verify the correctness of theoretical analysis.

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Jiaxuan Liu, Zhongjian Kang, and Yisen Sun "Research on electric anti-shake technology of power grid system of chemical enterprise based on process immune time", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 1229409 (19 October 2022); https://doi.org/10.1117/12.2639875

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KEYWORDS

Industrial chemicals

Mathematical modeling

Data modeling

Tolerancing

Fluctuations and noise

Power supplies

Resistance

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