Authors: D. Anghinolfi, C. Nattero, M. Paolucci, L.M. Gambardella, R. Montemanni, N.E. Toklu
With the growth in the demand for electrical energy globally, optimization of power plant productions and power plant maintenance scheduling have become important research topics. In this paper a Large Scale Energy Management (LSEM) problem is studied, where two types of power plants are considered. Power plants of the first type can be refueled while still operating. Power plants of the second type are
nuclear plants, which need to be shut down from time to time, for refueling and maintenance. Considering these two types of power plants, LSEM is the problem of optimizing production plans and scheduling of maintenances of nuclear plants, with the objective of keeping the production cost as low as possible. In this article, a matheuristic optimization approach based on the successive solutions of simplified sub-problems guided by a local search exploration is proposed to solve LSEM. The approach involves mixed integer linear programming and simulated annealing optimization methods. Computational results on some realistic instances are presented.
Keywords: optimization, large-scale energy management, matheuristics algorithms; mixed integer linear programming; simulated annealing.