NSGA-II Algorithms for Multi-Objective Short-Term Hydrothermal Scheduling

Hydraulic coupling between hydropower plants, time of delay with downstream flow and possible causes such as wasting water, must consider in the optimal scheduling of cascade hydropower plants containing hydro and thermal units. Present a multi-objective model considering environment protection and saving energy. This model takes total operating costs of thermal power plants, contaminative gas emission and spilling water of hydro units as optimum objectives. Fast Non-dominated sorting genetic algorithm (NSGA-II), a new multi-objective genetic algorithm, is applied to the optimal scheduling model for the first time. The simulation results show that this proposal model increases generation benefits of hydropower units, reduces operating costs of thermal units, advances comprehensive benefits of power systems, and provides a novel research thought for hydrothermal power systems short-term optimal scheduling problems.