Intelligent swarm-based optimization technique for oscillatory stability assessment in power system

This paper discussed the prediction of oscillatory stability condition of the power system using a particle swarm optimization(PSO) technique. Indicators namely synchronizing(Ks)and damping(Kd) torque coefficients is appointed to justify the angle stability condition in a multi-machine system. PSO is proposed and implemented to accelerate the determination of angle stability. The proposed algorithm has been confirmed to be more accurate with lower computation time compared with evolutionary programming(EP) technique. This result also supported with other indicators such as eigenvalues determination, damping ratio and least squares method. As a result, proposed technique is achievable to determine the oscillatory stability problems.

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Oscillatory Stability Prediction Using PSO Based Synchronizing and Damping Torque Coefficients

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v7i3.961 ◽

2018 ◽

Vol 7 (3) ◽

pp. 331-344

Author(s):

Nor Azwan Mohamed Kamari ◽

I. Musirin ◽

Z. A. Hamid ◽

M. H. M. Zaman

Keyword(s):

Stability Condition ◽

Damping Ratio ◽

Computation Time ◽

Optimization Method ◽

Optimization Techniques ◽

Least Square ◽

Artificial Immune ◽

Angle Stability ◽

Damping Torque

This paper presents the assessment of stability domains for the angle stability condition of the power system using Particle Swarm Optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, PSO is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as Evolutionary Programming (EP) and Artificial Immune System (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.

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Optimal Tuning of SVC-PI Controller using Whale Optimization Algorithm for Angle Stability Improvement

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v12.i2.pp620-624 ◽

2018 ◽

Vol 12 (2) ◽

pp. 620

Author(s):

N. A. M. Kamari ◽

I. Musirin ◽

Z. A. Hamid ◽

A. A. Ibrahim

Keyword(s):

Optimization Algorithm ◽

Damping Ratio ◽

Optimization Technique ◽

Computation Time ◽

Synchronous Generator ◽

Pi Controller ◽

Optimization Techniques ◽

Whale Optimization Algorithm ◽

Whale Optimization ◽

Angle Stability

This paper proposed a new swarm-based optimization technique for tuning conventional proportional-integral (PI) controller parameters of a static var compensator (SVC) which controls a synchronous generator in a single machine infinite bus (SMIB) system. As one of the Flexible Alternating Current Transmission Systems (FACTS) devices, SVC is designed and implemented to improve the damping of a synchronous generator. In this study, two parameters of PI controller namely proportional gain, KP and integral gain, KI are tuned with a new optimization method called Whale Optimization Algorithm (WOA). This technique mimics the social behavior of humpback whales which is characterized by their bubble-net hunting strategy in order to enhance the quality of the solution. Validation with respect to damping ratio and eigenvalues determination confirmed that the proposed technique is more efficient than Evolutionary Programming (EP) and Artificial Immune System (AIS) in improving the angle stability of the system. Comparison between WOA, EP and AIS optimization techniques showed that the proposed computation approach gives better solution and faster computation time.

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PSS Based Angle Stability Improvement Using Whale Optimization Approach

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v8.i2.pp382-390 ◽

2017 ◽

Vol 8 (2) ◽

pp. 382 ◽

Cited By ~ 2

Author(s):

N. A. M. Kamari ◽

I. Musirin ◽

Z. Othman ◽

S. A. Halim

Keyword(s):

Damping Ratio ◽

Optimization Technique ◽

Low Frequency ◽

Computation Time ◽

Synchronous Generator ◽

Optimization Techniques ◽

Humpback Whales ◽

Optimization Approach ◽

Whale Optimization ◽

Angle Stability

This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning PSS-LL parameters, a new technique called Whale Optimization Algorithm (WOA) is proposed. This method mimics the social behavior of humpback whales which is characterized by their bubble-net hunting strategy in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) in improving the angle stability of the system. Comparison between WOA, PSO and EP optimization techniques showed that the proposed computation approach give better solution and faster computation time.

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PSO-Based Oscillatory Stability Assessment by Using the Torque Coefficients for SMIB

Energies ◽

10.3390/en13051231 ◽

2020 ◽

Vol 13 (5) ◽

pp. 1231

Author(s):

Nor Azwan Mohamed Kamari ◽

Ismail Musirin ◽

Ahmad Nazri Dagang ◽

Mohd Hairi Mohd Zaman

Keyword(s):

Artificial Immune System ◽

Damping Ratio ◽

Evolutionary Programming ◽

Least Square ◽

Computational Time ◽

Stability Assessment ◽

Artificial Immune ◽

Swarm Optimization ◽

D Values

This study discusses the evaluation of oscillatory stability based on the synchronizing K s and damping K d torque coefficients for a single-machine system connected to an infinite bus (SMIB). Particle swarm optimization (PSO) technique is used to determine K s and K d values and subsequently identify the oscillatory stability conditions in the SMIB. The ability of PSO is compared with those of evolutionary programming (EP) techniques and artificial immune system (AIS). The least square (LS) method is selected as the benchmark for K s and K d values determined by PSO, EP, and AIS. Simulation results show that PSO successfully estimated K s and K d values closest to LS compared with EP and AIS. PSO also uses lower computational time compared with those of the two other techniques. The proposed technique is suitable for solving oscillatory stability problems based on the determination of eigenvalues and minimum damping ratio.

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