Abstract
Real coded genetic algorithm (RCGA) and improved real coded genetic algorithm (IRCGA) have been applied for the solution of short-term hydrothermal scheduling problem. The improved technique has been developed and tested on a multi reservoir cascaded hydroelectric system having generation-load power balance, upper and lower limits on reservoir capacity, water discharge rate, water spillage rate, hydraulic continuity restriction and operating capacity limits of different hydro and thermal units. The water transport delay between connected reservoirs has also been taken into consideration. The performance of the proposed approach is validated with four test systems. The results of the proposed algorithm are compared with those of modified differential evolution (MDE), teaching learning-based optimisation (TLBO), clonal selection algorithm (CSA), improved fast evolutionary programming (IFEP), improved particle swarm optimisation (IPSO), and genetic algorithm (GA). From numerical results, it has been found that the IRCGA-based approach is able to provide better solutions in lesser computational time.
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