Abstract:
This work investigates the state distributions of failure rate, performance curve, maintenance cost and preventive frequency of the transformer population through the Markov Model (MM). The condition parameters data of the oil samples known as Oil Quality Analysis (OQA), Dissolved Gas Analysis (DGA), Furanic Compounds Analysis (FCA) and age were analyzed from 370 distribution transformers. This work utilized the computed failure rate prediction model of the transformer population based on MM using the nonlinear minimization technique. First, the transition probabilities for each state were adjusted based on pre-determined maintenance repair rates of 10%, 20%, and 30%. Next, the failure rate state distributions and performance curves at various states were analyzed. Finally, the maintenance costs and preventive maintenance frequency were estimated utilizing the proposed maintenance policy models and the failure rate state probabilities. The result reveals that the transition from state 2 to state 1 with a 30% pre-determined maintenance repair rate can provide an average reduction of failure rate up to 11%. Based on the failure rate state probability, an average increment of maintenance cost from RM 18.32 million to RM 251.87 million will be incurred over 30 years. In total, 85% of the transformer population must undergo maintenance every nine months to avoid reaching very poor conditions.
