Novel Method for Comprehensive Corrosion Evaluation of Grounding Device

Abstract

Tower grounding device provides the discharging channel for fault currents, ensuring the safe and reliable operation of transmission lines. However, the carbon steel tower grounding device is prone to corrosion, which affects the discharging performance and causes potential safety hazards. Existing evaluation methods are divided into subjective evaluation through excavating grounding device and objective evaluation through experimental detection. However, these methods suffer from poor accuracy in the evaluation results. In order to solve the above-mentioned problems, this paper proposed a comprehensive evaluation method for corrosivity of grounding device based on fuzzy theory, taking soil resistivity, PH value, water content and salt content as evaluation factors, and integrating subjective and objective weights based on game theory, which realizes complementary advantages of subjective and objective methods. Finally, a comprehensive evaluation algorithm for the grounding device corrosion is formed. Experiments are conducted to validate the effectiveness and accuracy of the proposed method.

Analysis of corrosion detection error of grounding grid under amplitude characterization

“…Accurate detection of grounding grid topology and corrosion is an important basis for measuring the condition of the grounding grid [9,10]. The surface magnetic field method, as a non-destructive testing method, generates a magnetic field at the surface of the ground by injecting and withdrawing electric current through the lead wires in the grounding grid so that current flows in the grid.…”

Novel method for power system synthesis load identification

“…With the improvement of the load model structure, the synthesis load model considering the impedance of the distribution network has been widely used [5,6]. Therefore, the linear methods used to identify the synthe- [7]. A simplified model identification strategy based on parameter sensitivity analysis was proposed in the literature [8], and genetic algorithm was used for parameter identification.…”

“…IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology sis load model had the problems of convergence difficulty and poor identification accuracy. With the development of computers and algorithms, various nonlinear intelligent optimization algorithms are studied [7]. A simplified model identification strategy based on parameter sensitivity analysis was proposed in the literature [8], and genetic algorithm was used for parameter identification.…”