The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON POWER SYSTEMS
Transactions ID Number: 89-720
Full Name: Abdullah Abusorrah
Position: Assistant Professor
Age: ON
Sex: Male
Address: P. O. Box: 3713 , Jeddah 21481
Country: SAUDI ARABIA
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E-mail address: aabusorrah@hotmail.com
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Title of the Paper: An improved Genetic algorithm for optimal power flow
Authors as they appear in the Paper: Abdullah M. Abusorrah , Abdel-Fattah Attia , Yusuf Al-Turki
Email addresses of all the authors: aabusorrah@hotmail.com, attiaa1@yahoo.com, yaturki@yahoo.com
Number of paper pages: 10
Abstract: This paper proposes an approach for optimum reactive power dispatch throughout the power network, using Genetic Algorithms (GA). Varying the crossover probability rate Pc and mutation probability rate Pm, the GA control parameters provide faster convergence than constant probability rates. The active power loss is minimized using six controlled system variables (generator voltages, transformer taps and shunt capacitors). The proposed method is evaluated on the practical Ward-Hale 6-bus system and the IEEE 14-bus power system. The Optimal Power Flow (OPF) is solved by a classical nonlinear optimization technique as well as the proposed linear adaptive genetic technique. Numerical results are presented and compared with published results.
Keywords: Reactive power control; optimal power flow; adapted genetic algorithm
EXTENSION of the file: .pdf
Special (Invited) Session: Optimal Power Flow Based on Linear Adapted Genetic Algorithm
Organizer of the Session: 642-432
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