Search

This study evaluates the Loss-of-Life (LOL) based on the modified relative aging rate of an Oil Natural Air Natural (ONAN) transformer with voltage and power ratings of132/33 kV and 60 MVA. The study's methodology included the determination of the Hotspot Temperature (HST) based on the differential equation in IEC 60076-7. The loading and ambient temperature profiles for HST determination are forecasted based on the Seasonal Autoregressive Integrated Moving Average (SARIMA). Next, a new relative aging rate was developed based on the Arrhenius equation, considering the pre-exponential factors governed by oxygen, moisture in paper, and acids at different content levels. The LOL was computed based on the new relative aging rate. The study's main aim is to examine the impact of pre-exponential factors on the LOL based on modified Arrhenius and relative aging rate. The results indicate that the LOLs for different conditions increase as the oxygen, moisture, low molecular weight acid (LMA), and high molecular weight acid (HMA) increase. The LOLs are 46 days, 1,354 days, and 2,662 days in the presence of 12,000 ppm, 21,000 ppm, and 30,000 ppm of oxygen. In 1%, 3%, and 5% moisture, the LOLs are 477 days, 2,799 days, and 7,315 days. At 1% moisture, the LOL is 1,418 days for LMA, while for HMA, it is 122 days. The LMA has the highest impact on the LOL compared to other aging acceleration factors. [ABSTRACT FROM AUTHOR]

This paper investigates the behaviour of partial discharge (PD) in transformer insulation paper based on the Finite Element Method (FEM). The three-dimensional (3D) FEM model consists of conductor and insulation paper, representing part of a transformer’s high voltage winding. The conductor’s width, height, and length used in this study were 2.4 mm, 11.5 mm, and 16 mm. An insulation paper thickness of 1 mm was modelled around the conductor. An internal cavity with a diameter of 0.5 mm cavity was introduced within the insulation paper. This study introduced two locations of the spherical cavities at the centre and left corner of the insulation paper: Location 1 (L1) and Location 2 (L2). An AC voltage of 33 kV, 50 Hz, was applied to the conductor while the bottom of the insulation paper was grounded. The model was used to study the electric field distribution within the insulation paper and its effect on PD current and charge magnitude. The influence of cavity location on the charge magnitude was also examined. It is found that the electric field distribution is influenced by the conductor configuration as well as the location of the cavity. The electric field in the cavity is the highest at L1 compared to L2. The first PD occurs faster for the cavity with a high electric field. Due to the PD occurrence at the same inception field, the real PD current and charge magnitude is similar at different locations. The apparent PD current and charge magnitude induced at the ground electrode is slightly higher at L1 than at L2. [ABSTRACT FROM AUTHOR]

This work examines the failure rate of the transformer population through the application of the Markov Model (MM) and Health Index (HI). Overall, the condition parameters data extracted from 3,192 oil samples were analysed in this study. The samples were from 370 transformers with the age range between 1 and 25 years. First, both HIs and failure rates of transformers were determined based on the condition parameters data of the oil samples known as Oil Quality Analysis (OQA), Dissolved Gas Analysis (DGA), Furanic Compounds Analysis (FCA) and age. A two-parameter exponential function model was applied to represent the relationship between the HI and failure rate. Once the failure rate state was obtained, the non-linear optimisation was used to determine the transition probability for each age band. Next, the future failure rate of the transformer population was computed through the MM prediction model. The goodness-of-fit test and Mean Absolute Percentage Error (MAPE) were utilised to determine the performance of the predicted failure rate. The current study reveals that the future state of the transformer population and failure rate could be predicted through MM based on updated transition probabilities. It is observed that the MAPE between predicted and computed failure rates is 7.3%. [ABSTRACT FROM AUTHOR]