A modified hybrid differential evolution for short-term scheduling of hydrothermal power systems with cascaded reservoirs

This paper presents a new approach for short-term hydrothermal scheduling of cascaded reservoirs using a modified hybrid differential evolution (MHDE) algorithm. Hydrothermal scheduling involves optimization of a non-linear objective function with a set of system and hydraulic constraints. In this paper the hybrid differential algorithm is modified in order to handle the equality constraints especially reservoir end volume and power balance constraints. The hybrid differential evolution in combination with a novel equality constraint handling mechanism provides better solution at a lesser computational effort. To show the efficiency of the proposed algorithm different case studies are carried out considering valve-point effects, prohibited discharge zones, multiple thermal units and transmission losses. The results of the proposed approach are compared with those of dynamic programming, non-linear programming, genetic algorithm, evolutionary programming and particle swarm optimization techniques. The results of the proposed algorithm are compared with differential evolution (DE) and its variants. From the numerical results it is found that the MHDE based approach is able to provide better solution at a relatively lesser computational effort.