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.

Electrically driven separation (EDS) technology with a high voltage (HV) alternating current source (AC) was used to remove glycerol and other contaminants from biodiesel in order to meet the ASTM D6751 and EN 14214 standards. Biodiesel was produced from a transesterification of refined palm oil and methanol using sodium methylate as a homogeneous catalyst. The effects of an Iron (Fe) electrode, including types of electrode configurations, vertical distance between electrodes, applied voltage, and separation time, were studied. Furthermore, the effects of the remaining catalyst and soap content in biodiesel phase were also investigated to improve the separating performance using the EDS technique. The EDS using HVAC and low amperage with a point-to-point electrode configuration showed the highest separation efficiency of 99.8%. The optimum vertical distance between electrodes was 3 cm, while the optimum applied voltage was 3 kV. The separation time of 240 s yielded the best separating performance, completely eliminating the unreacted catalyst, and the lowest of the normalized remaining soap value content was obtained. Considering all of this, the EDS technique had higher efficiency to remove glycerol and other contaminants than a conventional separation of gravitation settling. The final biodiesel product was produced with the high purity of 98.0 wt% after purification and met all standard specifications.

In this paper, a lifetime estimation method for underground cable systems is proposed by combining a health index (HI) and conditional factor (CF). The underground cable system consists of underground cable, joint, termination, manhole, and duct bank. The HI is an indicator to indicate the actual condition of underground cable components and systems whereas the CF is used to indicate different operating stresses of the system under different operating conditions such as percentage loading, electrical stresses, laying structure, environment, etc. The actual technical data as well as historical operating and testing records are applied. The weighting and scoring method with the analytical hierarchy process are used to classify an importance of underground cable components, testing methods, and criteria used in the HI and CF calculation. The annual calculated HIs are plotted to investigate the lifetime trending curve by using a polynomial function. The degradation curve based on calculated CF is estimated by using the Weibull distribution function. Finally, the remaining life of the underground cable system is determined by matching the lifetime trending curve with the degradation curve. Ten practical underground cable systems supplying power in a high voltage power delivery system are evaluated with effective results. The lifetime of the underground cable system can be successfully estimated.

In this paper, a modeling method for estimating the remaining useful life (RUL) of aged underground cable systems is proposed that uses statistical health index (HI) and operating factor (OF) data of retired systems. The HI is an indicator which identifies the condition of an underground cable system and its components and is calculated from testing and inspection results. The OF takes actual operating conditions and technical data from the system into consideration. Both factors are then combined to determine the overall health index (OHI) of each system. For RUL estimation of underground cable systems, normal distribution and Weibull distribution analyses are first applied to determine a health index curve and an aging line. The relationship between these two curves gives an estimate of the system’s apparent age. The RUL of the system is then calculated in terms of the difference between its apparent age and its actual chronological age. In this study, thirteen retired systems and ten operating systems were evaluated and analyzed, and accurate results were obtained. Using the methods described here, the apparent age and the RUL of underground cable systems can be accurately estimated. Finally, a maintenance strategy for underground cable systems is recommended, which promises more efficient maintenance and greater cost-effectiveness in the management of underground cable systems.

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.