Development of a Hybridized Model for Predicting the Life Span of Power Transformers

Power transformers are important equipment of the electrical switchyard whose failure leads to long hours of outage. In this research, a two-stage hybridized model for determining the lifespan of power transformers is presented by using the furan content to determine the Degree of  Polymerisation (DP) of transformer. For a ‘virgin’ transformer, the furan content was about 0.01ppm while a transformer with about 10ppm was within its end of useful life. 2-Furaldehyde (2FAL) content values of  0.01ppm and 10ppm correspond to DP values of approximately 1200 and 250, respectively. These parameters were used in developing a DP model using Jacobi and Gauss Seidel numerical analysis iterative techniques. The techniques were implemented in Matrix Laboratory 8.2 (R2013b)  environment. The second stage involved the hybridisation of the developed DP model with another rate constant model adopted from Arrhenius. This stage was also implemented in Matrix Laboratory 8.2 (R2013b)  environment. The life span of the transformer was determined by adding the service age at any point in time to the remaining lifetime at that point. A GUI of the hybridised model was developed using SIMULINK blocks. The developed model yielded a DP range of 247 ≤ DP ≤ 1184. Factors such as the hotspot temperature, activation energy and pre-exponential factor were useful for the determination of lifespan.Keywords: Degree of Polymerization, Furan Content, Life Expectancy, Power Transforme

Reliability assessment of a gas generating station in Ogun State, Nigeria

This study evaluates and presents the reliability and availability of a power plant, Akute Power Plant, Ogun State, Nigeria, during the period of January – December, 2015. Time series load data on each generating unit were collected from Akute Power Plant daily operational log book from January to December 2015. Outages were classified into types, frequency and durations. The operational data for the above period was collected and analyzed using Reliability methods. Reliability conditions are defined with the collected data and types of the failure faced by each generating units. The most important reliability indices like mean time to repair (MTTR), mean time to failure (MTTF), mean time between failures (MTBF), repair rate (μ), failure rate (λ) were determined based on the loss of load approach. The reliabilities of each generating unit were evaluated on monthly basis for one year and the average availability of G1, G2, G3, and G4 were 0.9701, 0.9726, 0.9767, and 0.9707 respectively, while the reliability indices for G1, G2, G3, and G4 were 0.9860, 0.9880, 0.9854, and 0.9840 respectively. Suggestions were made to minimize system unavailability in order to improve the reliabilities of the network.Keywords: Reliability Methods, Mean Time To Repair, Mean Time Between Failure, Failure Rat