Within a yearly horizon, a transmission system operator needs to schedule the maintenance outages of the set of transmission lines due for maintenance. Facing this task, two conflicting objectives arise: on one hand, the system security should be preserved as much as possible, and, on the other hand, market operation should be altered in the least possible manner. To address this scheduling problem, a bilevel model is proposed whose upper-level problem schedules line maintenance outages seeking maximum system security. This upper-level problem is constrained by a set of lower-level problems that represent the clearing of the market for all the time periods considered within the yearly planning horizon. This bilevel model is conveniently converted into a nonlinear mathematical program with equilibrium constraints (MPEC) that can be recast as a mixed-integer linear programming problem solvable with currently available branch-and-cut techniques. After setting the maintenance schedule for transmission lines, the Transmission System Operator needs to set the maintenance schedule for all generators in the power system. Since generators are owned by different power producers, the optimal schedules for generators preventive maintenance has to be transparent and nondiscriminatory. Profit maximization objectives of each power producer have to be taken into account, but constraining these objectives by technical security requirements. To solve this problem, a bilevel mathematical model in the MPEC form is proposed. The upper-level problem contains generating unit scheduling constraints, while the lower-level problem simulates the market clearing process. Since each MPEC corresponds to a single generator maintenance scheduling problem, MPECs for each generator are solved cyclicly in order to achieve equilibrium, making this problem an equilibrium problem with equilibrium constraints (EPEC). The equilibrium, which may or may not exist, is achieved if non of the producers is able to increase its profit by changing the maintenance time periods of its generating units. This is known as the diagonalization procedures which often leads to local optimal point. The characterization of these local optimal points is the important issue of this doctoral thesis.