Abstract
Effective Partial Discharge (PD) localization can detect the insulation problems of the power equipment in a substation and improve the reliability of power systems. Typical Ultra-High Frequency (UHF) PD localization methods are mainly based on time difference information, which need a high sampling rate system. This paper proposes a novel PD localization method based on a received signal strength indicator (RSSI) fingerprint to quickly locate the power equipment with potential insulation defects. The proposed method consists of two stages. In the offline stage, the RSSI fingerprint data of the detection area is measured by a wireless UHF sensor array and processed by a clustering algorithm to reduce the PD interference and abnormal RSSI values. In the online stage, when PD happens, the RSSI fingerprint of PD is measured via the input of pattern recognition for PD localization. To achieve an accurate localization, the pattern recognition process is divided into two steps: a preliminary localization is implemented by cluster recognition to reduce the localization region, and the compressed sensing algorithm is used for accurate PD localization. A field test in a substation indicates that the mean localization error of the proposed method is 1.25 m, and 89.6% localization errors are less than 3 m.
Highlights
Partial Discharge (PD) is the representation of the insulation degradation of the power equipment in a substation, which can give rise to equipment failure and even serious accidents [1,2]
Typical Ultra-High Frequency (UHF) methods are mainly based on time or angle information of the UHF signals such as time of arrival (TOA) [8], time difference of arrival (TDOA) [9,10], and angle of arrival (AOA) [11,12]
In this paper [13,14] we proposed a PD localization method in transformers based on TDOA
Summary
Partial Discharge (PD) is the representation of the insulation degradation of the power equipment in a substation, which can give rise to equipment failure and even serious accidents [1,2]. In this paper [13,14] we proposed a PD localization method in transformers based on TDOA. In the online recorded to establish the RSSI fingerprint map of the detection area. UHF sensors sensors array and and used to to estimate the location of by pattern recognition in the prebuilt fingerprint map. The preliminary localization is implemented by cluster recognition, which produces a small RSSI fingerprint map. The built RSSI fingerprint map will be divided into several clusters by this clustering algorithm for the preliminary localization in the online stage, as described above. A field test is performed in a substation to verify the effectiveness of our proposed PD localization method.
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