This paper proposes a comprehensive procedure to assess the condition of gas insulated switchgear (GIS) equipment by using the conventional weight and score method and introducing a conditional factor to improve the accuracy of the health index evaluation. Generally, the inspection and testing of GIS components are conducted according to manufacturer recommendations and guidelines in the international standards. However, this raw data has not been simplified and systematically processed for condition assessment. The score and weight technique are applied to transform the physical condition according to visible and measurable aging to numerical values in terms of component and bay health index values. The accuracy of the obtained health index has been improved by a conditional factor, which considers invisible aging factors, such as age, number of switching operations, degree of satisfactory operation, obsolescence, and adequacy of the interrupting rating. Here, a condition evaluation procedure has been developed and compared with the fuzzy logic method and the health index dominant score technique with satisfactory results. Subsequently, the proposed procedure has been developed as web application software to evaluate 175 bays of GIS in both 115 and 230 kV networks of an independent power producer supplying electricity of 3094 MW to a large industrial estate in Thailand. Eight GIS bays showed moderate or poor condition and the proper actions were assigned to prevent their failure. The software is in use in practice as a decision support tool to effectively manage the maintenance tasks and to improve supply reliability.

This paper presents a fuzzy logic approach, a simplified and adaptable method, to determine the health index of gas-insulated switchgear (GIS) bay and their compartments. Since the traditional weighting and scoring method (WSM) is a subjective method, the fuzzy logic approach has been applied to enhance the accuracy of the health index (HI) determination by evaluating the detectable degradation and the incorporated conditional factor (CF) considering actual operating conditions and invisible ageing. The input data are first obtained from routine inspection and time-based testing and then converted to numerical values as the fuzzy logic model input to compute the component HI. The bay HI values are further calculated by applying the WSM using the obtained component of the HI. Then, the accuracy of the obtained HI of the bay has been improved by multiplying with the CF to obtain the overall bay HI values. The proposed methodology was implemented in an independent power producer in a large industrial estate in Thailand to evaluate 175 GIS bays with actual data. The results were compared against other HI evaluation techniques with a satisfactory outcome. Finally, the overall bay HI is used to prioritize maintenance activity, to effectively allocate human resources, to prevent unplanned outages, and to achieve cost-effective, condition-based maintenance.

This paper presents condition assessment of medium voltage underground cable system. Various testing methods and diagnostic techniques are presented to find a defect of individual underground cable components such as withstand voltage, partial discharge, dielectric loss or tan delta, and visual inspection. Subsequently, technical criteria for condition evaluation is defined. Then condition assessment is carried out by applying the weighting and scoring method to determine health index of underground cable components and cable system. Finally, the overall health index is modified by a conditional multiplying factor to incorporate the influences of practical operating condition and installation type. The overall health index enables the utility to prioritize the preventive and condition-based maintenance of underground cable system.