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Performance Comparison of GA, DE, PSO and SA Approaches in Enhancement of Total Transfer Capability using FACTS Devices
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 Title & Authors
Performance Comparison of GA, DE, PSO and SA Approaches in Enhancement of Total Transfer Capability using FACTS Devices
Chandrasekar, K.; Ramana, N.V.;
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In this paper the performance of meta-heuristics algorithms such as GA (Genetic Algorithm), DE (Differential Evolution), PSO (Particle Swarm Optimization) and SA (Simulated Annealing) for the problem of TTC enhancement using FACTS devices are compared. In addition to that in the assessment procedure of TTC two novel techniques are proposed. First the optimization algorithm which is used for TTC enhancement is simultaneously used for assessment of TTC. Second the power flow is done using Broyden - Shamanski method with Sherman - Morrison formula (BSS). The proposed approach is tested on WSCC 9 bus, IEEE 118 bus test systems and the results are compared with the conventional Repeated Power Flow (RPF) using Newton Raphson (NR) method which indicates that the proposed method provides better TTC enhancement and computational efficacy than the conventional procedure.
Differential evolution;Genetic algorithm;Particle swarm optimization;Simulated annealing and total transfer capability;
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개선된 수업-학습기반 최적화 알고리즘을 이용한 자기부상 제어기의 최적 설계,조재훈;김용태;

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