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Go to Editorial ManagerCrow Search Algorithm is an innovative meta- heuristic optimization algorithm. In this paper, chaotic maps are combined into Crow Search Algorithm to increase its global optimization. Ten variant chaotic maps are used and the Tent map is found as the best choices for high dimensional problems. The novel Chaotic Crow Search Algorithm is relied on the substitution of a random location of search space and the awareness parameter of crow with chaotic sequences. The results show that the chaotic maps are able to enhance the performance of the Crow Search Algorithm. Also the novel Chaotic Crow Search Algorithm outperforms the conventional Crow Search Algorithm, first version of Chaotic Crow Search Algorithm, Genetic Algorithm, and Particle Swarm Optimization Algorithm from the point view of speed convergence and the function dimensions.
In this paper, energy and exergy concepts have been carried out on one of the largest gas turbine power plants in Iraq (Rumaila-Basra). Both ISO operating conditions as well as actual operating data recorded for one month in hot season are considered. Results indicate that a lot of heat energy accompanied with remarkable exergy is discharged to the atmosphere. Also, it is found that the combustion chamber has the largest exergy destruction among the plant components. Possibility of cooling the intake air drawn by the compressor and its effects on the plant performance is studied. The required cooling load is found to be in the range 3379 T.R for part load operation to 4723.3 T.R for full load operation.