Symbiotic organisms search algorithm for short-term hydrothermal scheduling

Hydrothermal scheduling is an important issue in the field of power system economics. The aim of the short-term hydrothermal scheduling is to optimize the hourly output of power generation for different hydrothermal units for certain intervals of time in order to minimize the total cost of generations. In this paper, a new meta-heuristic technique, symbiotic organisms search is implemented to solve short-term hydrothermal scheduling problem. The word "symbiosis" defines the relationship between two different species. The relationships are mutualism, commensalism and parasitism, depending on which the algorithm works. To investigate its computational efficiency, symbiotic organisms search algorithm is employed to three test systems. The results obtained by the symbiotic organisms search algorithm are compared with those obtained by many recently developed optimization techniques such as evolutionary programming, genetic algorithm, differential evolution, teaching-learning based optimization, oppositional real coded chemical reaction based optimization and modified dynamic neighborhood learning based particle swarm optimization. (C) 2016 Ain Shams University.