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Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods

عنوان مقاله: Solving OPF problem with the Hybrid GA and the Hybrid PSO Algorithms and Comparing with the Gradient-based Methods
شناسه ملی مقاله: PSC21_202
منتشر شده در بیست و یکمین کنفرانس بین المللی برق در سال 1385
مشخصات نویسندگان مقاله:

Mostafa Majidpour - School of Electrical & Computer Engineering University of Tehran, Iran
Ashkan Rahimi-Kian - School of Electrical & Computer Engineering University of Tehran, Iran

خلاصه مقاله:
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).

کلمات کلیدی:
Optimal Power Flow (OPF), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Newton's Method, Hybrid GA, Hybrid PSO

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/19786/