Partial Discharge Direction of Arrival Estimation in Air-insulated Substation by UHF Wireless Array and RSSI Maximum Likelihood Estimator

TL;DR

This paper presents a cost-effective, portable method for localizing partial discharges in air-insulated substations using a UHF wireless sensor array and maximum likelihood estimation, achieving high accuracy without high sampling rates.

Contribution

It introduces a novel PD direction of arrival estimation method combining UHF wireless sensors, RSSI, and statistical algorithms, reducing cost and complexity compared to traditional TDOA methods.

Findings

Average DOA error less than 6 degrees

Enhanced portability and cost-effectiveness

Validated through laboratory testing

Abstract

The quick detection and localization of partial discharge (PD) in an air-insulated substation (AIS) based on ultrahigh-frequency (UHF) sensor arrays are efficient for power equipment monitoring. The adopted UHF PD time difference of arrival (TDOA) methods mainly use the time difference of electromagnetic wave signals. Thus, the system requires both a high sampling rate and time synchronization accuracy, leading to a high cost and large size. In this study, the feasibility and accuracy of PD DOA in an AIS were investigated using a UHF wireless sensor array and the received signal strength indicator. First, the power pattern of the designed UHF wireless sensor array was obtained via an offline experiment. Then, a statistical approach to the PD DOA method based on the maximum likelihood estimator was employed to obtain the preliminary DOA result. Finally, interpolation and clustering algorithms were used to improve the accuracy of the DOA. A laboratory test was conducted. The average error of the PD DOA was less than 6{\deg}, and the cost-effectiveness and portability were clearly improved.