A Markov model of generator performance at the Kainji hydro-power station in Nigeria

Abstract

The Kainji hydropower station is a seven turbo-alternator station that for many years served as the base load supply for the Nigerian power grid. Over 200,000 pieces of data about the performance of the machines were used to estimate values of the failure and repair rates for each machine and a Markov steady-state model of the plant was constructed to determine the probability output of the turbines. This result showed that Kaplan turbine (KT) 12 is prone to failure compared to any other KT unit in the hydropower plant. Also, the clusters of probability that define the system state due to the different output capacities of the units show that the hydropower plant has not performed to its maximum capacity, further evaluation shows that 60% of the KT machine units are operating which is consistent with the observed robustness of the output. The model not only conforms to observations but reasonably provide a means of studying the effects of different actions that may be taken to improve the performance of hydropower plant.