DAILY GENERATION SCHEDULING OPTIMIZATION WITH TRANSMISSION CONSTRAINTS - A NEW CLASS OF ALGORITHMS

The paper describes a new class of algorithms dealing with the Daily Generation Scheduling (DGS) problem. These algorithms have been designed by: - adding artificial constraints (and variables) to the original optimization problem, -handling these artificial constraints using a dual approach, - using an Augmented Lagrangian technique rather than a standard Lagrangian relaxation technique, - applying the Auxiliary Problem Principle which enables to cope with the nonseparable terms introduced by the Augmented Lagrangian. To deal with the DGS optimization problem these algorithms are shown as more effective than classical ones. Furthermore, they are well suited to solve this DGS problem taking into account transmission constraints, and thus open new fields of investigations and applications.