Surveillance Test Interval optimization for nuclear plants using Real Parameter Genetic Algorithms

Surveillance Test Interval is an important parameter for the standby systems of a plant with respect to its availability, cost and other issues. Stand-by systems are not required during normal operations but are essentially required when demanded by the plant operations. Stand-by systems are tested and maintained periodically in order to ensure their serviceability. In this paper an attempt has been done to optimize the unavailability, cost and manrem consumption with respect to Surveillance Test Interval for the standby systems of nuclear plants. In this work a novel approach has been introduced where Real Parameter Genetic Algorithm (GA) has been used for the multi-objective optimization problem in hand. Application of Genetic Algorithms in similar problems has been reported in literature. But the approach proposed in this paper differs from the exixting methods significantly. In this work real-parameter GA has been used which makes the algorithm simple by not having the overhead of encoding and decoding of solutions. More-over a multi-objective optimization method has been proposed that not only takes care of optimizing the unavailability but also cost and manrem consumption. Here we have mainly concentrated on the Emergency Core Cooling System of a Research Reactor, but the same idea can easily be extended for the other standby systems.