Artificial Bee Colony Optimization of AGC in a Two-area Interconnected Power System
16th International Middle- East Power Systems Conference -MEPCON'2014 Ain Shams University, Cairo, Egypt, December 23 - 25, 2014 • 2014
Publication Information
Authors
M. Elsisi, M. Soliman, W. Mansour
Keywords
Artificial Bee Colony (ABC), Genetic
Algorithms (GAs), Load Frequency Control (LFC), PI Controller.
Journal
16th International Middle- East Power Systems Conference -MEPCON'2014 Ain Shams University, Cairo, Egypt, December 23 - 25, 2014
Publisher
Not Available
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Not Available
Supplementary Materials
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Abstract
Artificial Bee Colony (ABC) has recently been
explored to develop a novel algorithm for distributed optimization
and control. This paper proposes an ABC-based Load Frequency
Control (LFC) design to enhance the damping of oscillations in a
two-area power system. A two-area non-reheat thermal system is
considered to be equipped with proportional plus integral (PI)
controllers. The proposed design problem is formulated as an
optimization problem. ABC is utilized to search for optimal
controller parameters by minimizing a time-domain based
objective function. The performance of the proposed controller
has been evaluated with the performance of the conventional PI
controller, and PI controller tuned by genetic algorithm (GA)
in order to demonstrate the superior efficiency of the proposed
ABC in tuning PI controller. Simulation results emphasis on the
better performance of the optimized PI controller based on ABC
in compare to optimized PI controller based on GA and
conventional one over wide range of operating conditions, and
system parameters variations.
explored to develop a novel algorithm for distributed optimization
and control. This paper proposes an ABC-based Load Frequency
Control (LFC) design to enhance the damping of oscillations in a
two-area power system. A two-area non-reheat thermal system is
considered to be equipped with proportional plus integral (PI)
controllers. The proposed design problem is formulated as an
optimization problem. ABC is utilized to search for optimal
controller parameters by minimizing a time-domain based
objective function. The performance of the proposed controller
has been evaluated with the performance of the conventional PI
controller, and PI controller tuned by genetic algorithm (GA)
in order to demonstrate the superior efficiency of the proposed
ABC in tuning PI controller. Simulation results emphasis on the
better performance of the optimized PI controller based on ABC
in compare to optimized PI controller based on GA and
conventional one over wide range of operating conditions, and
system parameters variations.
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