TY - JOUR
T1 - An efficient particle swarm optimization technique with chaotic sequence for optimal tuning and placement of PSS in power systems
AU - Eslami, Mahdiyeh
AU - Shareef, Hussain
AU - Mohamed, Azah
AU - Khajehzadeh, Mohammad
N1 - Funding Information:
The authors are grateful to National University of Malaysia (UKM) for supporting this study under grants DIP-2012-30 and UKM-DLP-2011-059.
PY - 2012/12
Y1 - 2012/12
N2 - This paper presents a novel and efficient method for the optimal tuning and placement of power system stabilizer (PSS). The proposed modified particle swarm optimization (MPSO) integrates the particle swarm optimization with passive congregation (PSOPC) and the chaotic sequence. Passive congregation helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search. In addition, the chaotic sequence concept is introduced to improve the global searching capability and prevent the premature convergence due to local minima. The proposed optimization procedure handles the problem-specific constraints, in this case it is related to low frequency oscillations in power systems and PSS, using a penalty function. Based on this, tuning and placement of PSS over a wide range of system configurations is formulated as a multi-objective function where the main objective is the aggregation of the three objectives related to the damping ratio and damping factor, and the number of PSS. The robustness of the proposed PSS tuning technique is verified on a multi-machine power system under different operating conditions. The performance of the proposed MPSO is also compared to the PSOPS and PSO, genetic algorithm through eigenvalue analysis, nonlinear time-domain simulation and statistical tests. Finally, the proposed method is applied to find out the best candidate machines to be equipped with PSSs. The obtained results showed that the new method can find the best placements and the optimum PSSs parameters simultaneously with an excellent global damping performance.
AB - This paper presents a novel and efficient method for the optimal tuning and placement of power system stabilizer (PSS). The proposed modified particle swarm optimization (MPSO) integrates the particle swarm optimization with passive congregation (PSOPC) and the chaotic sequence. Passive congregation helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search. In addition, the chaotic sequence concept is introduced to improve the global searching capability and prevent the premature convergence due to local minima. The proposed optimization procedure handles the problem-specific constraints, in this case it is related to low frequency oscillations in power systems and PSS, using a penalty function. Based on this, tuning and placement of PSS over a wide range of system configurations is formulated as a multi-objective function where the main objective is the aggregation of the three objectives related to the damping ratio and damping factor, and the number of PSS. The robustness of the proposed PSS tuning technique is verified on a multi-machine power system under different operating conditions. The performance of the proposed MPSO is also compared to the PSOPS and PSO, genetic algorithm through eigenvalue analysis, nonlinear time-domain simulation and statistical tests. Finally, the proposed method is applied to find out the best candidate machines to be equipped with PSSs. The obtained results showed that the new method can find the best placements and the optimum PSSs parameters simultaneously with an excellent global damping performance.
KW - Chaotic sequence
KW - Particle swarm optimization
KW - Passive congregation
KW - Placement
KW - Power system stabilizer
KW - Tuning
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U2 - 10.1016/j.ijepes.2012.07.028
DO - 10.1016/j.ijepes.2012.07.028
M3 - Article
AN - SCOPUS:84864749731
SN - 0142-0615
VL - 43
SP - 1467
EP - 1478
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
IS - 1
ER -