In this paper, a genetic algorithm and constriction factor based particle swarm optimization technique are proposed for solving the short term variable head hydrothermal scheduling problem with transmission line losses. The performance efficiency of the proposed techniques is demonstrated on hydrothermal test system comprising of two thermal units and two hydro power plants. the simulation results obtained from the constriction factor based particle swarm optimization technique are compared with the outcomes obtained from the genetic algorithm to reveal the validity and verify the feasibility of the proposed methods. The results show that the constriction factor based particle swarm optimization technique give the same results as obtained by genetic algorithm but the computation time of the constriction factor based particle swarm optimization method is less than genetic algorithm.
Keywords: - Hydrothermal Generation Scheduling, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Constriction Factor (CF)
A new grade of Al-Li alloy, C460, was solution treated at 550°C for 3 hours, cold water quenched, and then aged at 200oC for 24 hours. Heat treatment produced a precipitate. In tensile and fatigue tests the precipitate was sheared by moving planar dislocation bands in response to cyclic stress strain. Results show that the precipitate has a significant effect on the tensile and the low-cycle fatigue behavior and on the microstructural characterization. Also, the alloy appears to undergo cyclic hardening, saturation, and softening, especially at lower plastic strain amplitudes. Scanning and transmission electron microscopy revealed precipitates and planar dislocation bands forming during plastic deformation.
Keywords: - C460, dislocation, fatigue, precipitate, tensile.
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