Optimal power flow based on linear adapted genetic algorithm

Authors:
Abdullah M. Abusorrah;Abdel-Fattah Attia;Yusuf A. Al-Turki
Affiliations:
Electrical Technology Department, Technical and Vocational Training Corporation, Jeddah, Saudi Arabia;Deanship of Scientific Research, King Abdulaziz University, Jeddah, Saudi Arabia;Deanship of Scientific Research, King Abdulaziz University, Jeddah, Saudi Arabia
Venue:
AEE'10 Proceedings of the 9th WSEAS international conference on Applications of electrical engineering
Year:
2010

Citing 3
Cited 0

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Assessment of genetic algorithm selection, crossover and mutation techniques in reactive power optimization

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation

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Abstract

Reactive power planning is an optimization problem. Solving this problem requires finding an optimal solution that minimizes an objective function while satisfying certain constraints. This paper proposes an approach for optimum reactive power dispatch throughout the power network, using the Genetic Algorithms (GA). Varying the crossover probability rate Pc and mutation probability rate Pm, the GA's 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 applied to the practical Ward-Hale 6-bus system. The OPF is solved by a classical nonlinear optimization technique as well as the proposed linear adaptive genetic technique.