Abstract :
An algorithm based on simulated annealing and successive linear programming is applied to solve equilibrium cycle optimization problems for pressurized water reactors. In these problems, the core reload scheme is represented by discrete variables, while the cycle length as well as uranium enrichment and loading of burnable poison in each feed fuel assembly are treated as continuous variables. The enrichments are considered to be distinct in all feed fuel assemblies. The number of batches and their sizes are not fixed and also determined by the algorithm. An important feature of the algorithm is that all the parameters are determined by the solution of one optimization problem including both discrete and continuous variables. To search for the best reload scheme, simulated annealing is used. The optimum cycle length as well as uranium enrichment and loading of burnable poison in each feed fuel assembly are determined for each reload pattern examined using successive linear programming. Numerical results of equilibrium cycle optimization for various values of the effective price of electricity and fuel reprocessing cost are studied.
