Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods
Publish place: 21st International Power System Conference
Publish Year: 1385
Type: Conference paper
Language: English
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PSC21_202
Index date: 18 November 2006
Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods abstract
Abstract- In this paper we evaluate using the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) method for solving Optimal Power Flow (OPF) in large scale power systems. We have proposed the Hybrid GA (HGA) and the hybrid PSO (HPSO) methods to increase the convergence speed and to reduce the risk of divergence in critical system conditions (i.e. transmission line flow limits). The proposed method was tested with the IEEE 118-bus and 300-bus test systems and compared with one gradient-based algorithm (Newton's method).
Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods Keywords:
Optimal Power Flow (OPF) , Genetic Algorithm (GA) , Particle Swarm Optimization (PSO) , Newton's Method , Hybrid GA , Hybrid PSO
Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods authors
Mostafa Majidpour
School of Electrical & Computer Engineering University of Tehran, Iran
Ashkan Rahimi-Kian
School of Electrical & Computer Engineering University of Tehran, Iran
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