Optimal design of power-system stabilizers using particle swarm optimization
Tóm tắt
In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power-system stabilizers (PSSs) is proposed. The proposed approach employs a particle-swarm-optimization (PSO) technique to search for optimal settings of PSS parameters. Two eigenvalue-based objective functions to enhance system damping of electromechanical modes are considered. The robustness of the proposed approach to the initial guess is demonstrated. The performance of the proposed PSO-based PSS (PSOPSS) under different disturbances, loading conditions, and system configurations is tested and examined for different multimachine power systems. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed PSOPSSs to damp out the local and interarea modes of oscillations and work effectively over a wide range of loading conditions and system configurations. In addition, the potential and superiority of the proposed approach over the conventional approaches is demonstrated.
Từ khóa
#Particle swarm optimization #Power system simulation #Evolutionary computation #Algorithm design and analysis #Damping #Robustness #System testing #Power system analysis computing #Eigenvalues and eigenfunctions #Analytical modelsTài liệu tham khảo
10.1109/59.260822
10.1109/59.193836
10.1109/TPAS.1983.317930
10.1016/S0142-0615(97)00031-8
lim, 1985, design of stabilizers in multimachine power systems, Proc Inst Elect Eng C, 132, 146
10.1109/TPWRS.1987.4335165
10.1109/59.54540
10.1109/59.627836
10.1049/ip-gtd:19981689
10.1109/59.801907
10.1007/978-1-4613-1635-0
10.1109/TPAS.1983.317797
10.1109/TPAS.1969.292452
abido, 1997, Intelligent techniques approach to power system identification and control
10.1016/0165-0114(91)90211-8
10.1109/60.326467
10.1109/59.761886
10.1109/59.736272
sauer, 1998, Power System Dynamics and Stability
anderson, 1977, Power System Control and Stability
10.1109/TPAS.1981.316355
10.1016/S0142-0615(99)00004-6
fogel, 1995, Evolutionary Computation Toward a New Philosophy of Machine Intelligence
10.1109/60.875496
angeline, 1998, evolutionary optimization versus particle swarm optimization: philosophy and performance differences, Proc 7th Ann Conf Evolutionary Programm, 601
10.1109/ICEC.1997.592326
ozcan, 1998, analysis of a simple particle swarm optimization system, Intell Eng Syst Through Artif Neural Networks, 8, 253
shi, 1998, parameter selection in particle swarm optimization, Proc 7th Ann Conf Evolutionary Program, 591