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In complex high voltage components local insulation defects can cause partial discharges (PD). Especially in highly stressed gas insulated switchgear (GIS) these PD affected defects can lead to major blackouts. Today each PD activity on important insulation components causes an intervention of an expert, who has to identify and analyze the PD source and has to decide: Are the modules concerned to be switched off or can they stay in service? To reduce these cost and time intensive expert interventions, this contribution specifies a proposal which combines an automated PD defect identification procedure with a quantifiable diagnosis confidence. A risk assessment procedure is described, which is based on measurements of phase resolved PD pulse sequence data and a subsequent PD source identification. A defect specific risk is determined and then integrated within a failure probability software using the Farmer diagram. The risks of failure are classified into three levels. The uncertainty of the PD diagnosis is assessed by applying different PD sources and comparisons with other evaluation concepts as well as considering system theoretical investigations. It is shown that the PD defect specific risk is the key aspect of this approach which depends on the so called criticality range and the main PD impact aspects PD location, time dependency, defect property and (over) voltage dependency.
Dreisbusch et al. (Mon,) studied this question.
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