A Self-Decoupling Contactless Overvoltage Measurement Method Based on Optimization of Measuring Point

Contactless overvoltage measurement sensor has good foreground in the application of the power system, and however, the difference in the installation position of the sensor will directly affect the stability of the measurement system. Therefore, it is essential to improve the overall measurement effect by selecting an appropriate measuring point. In this article, first, we proposed a new self-decoupling method based on the simplified matrix with the position parameters of the measuring point and applied it in the measurement of three-phase transient overvoltage. Then, we obtained the 3-D electric field (E-field) distribution characteristic under the different simulated overvoltage signals and preliminarily analyzed the measuring effect of the various measuring points distributed in the axial and radial direction of the overhead line. Furthermore, we proposed the gradient optimizing method with a calculation and analysis process for the selection of the measuring point. Finally, taking the three-phase horizontal distributed transmission lines as an example, we calculated the voltage coefficient matrix at various selected points, estimated the uncertainty contributions, and accomplished the test through the overvoltage experimental platform. From the result, the relative amplitude error of the overvoltage signal measured by the sensor installed at the optimal measuring point is less than 3.50%, the relative expanded uncertainty of the test at the optimal point is about 8.74%, and the values are much smaller than those of other measuring points, which proved the effectiveness of the proposed method.

Automated summary

This article proposes a new self-decoupling method and analyzes the stability of the measurement system by measuring at different locations. Then, a gradient optimizing method is introduced to select the optimal measuring point, and the effectiveness of the proposed method is validated through experiments.