Coordinated AVR-PSS for Transient Stability Using Modified Particle Swarm Optimization

2014 ◽  
Vol 67 (3) ◽  
Author(s):  
J. Usman ◽  
M. W. Mustafa ◽  
G. Aliyu ◽  
B. U. Musa
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Transient Stability ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Operating Conditions ◽  
Computational Time ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Wide Range

This paper presents the coordination between the Automatic Voltage Regulator (AVR) and Power System Stabilizers (PSS) to increase the system damping over a wide range of systems’ operating conditions in order to improve the transient stability performance and steady state performance of the system. The coordinated design problem is formulated as an optimization problem which is solved using Iteration Particle Swarm Optimization (IPSO). The application of IPSO technique is proposed to optimize the parameters of the AVR and PSS to minimize the oscillations in power system during disturbances in a single machine infinite bus system (SMIB). The performance of the proposed IPSO technique is compared with the traditional PSO technique. The comparison considered is in terms of parameter accuracy and computational time. The results of the time domain simulations and eigenvalue analysis show that the proposed IPSO method provides a better optimization technique as compared to the traditional PSO technique.  

scholarly journals Enhancement transient stability of power system using UPFC with M-PSO

2020 ◽  
Vol 17 (1) ◽  
pp. 61
Author(s):  
Rashid H. AL-Rubayi ◽  
Luay G. Ibrahim
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Transient Stability ◽  
Electrical Power ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Simulation Results ◽  
The Stability

<span>During the last few decades, electrical power demand enlarged significantly whereas power production and transmission expansions have been brutally restricted because of restricted resources as well as ecological constraints. Consequently, many transmission lines have been profoundly loading, so the stability of power system became a Limiting factor for transferring electrical power. Therefore, maintaining a secure and stable operation of electric power networks is deemed an important and challenging issue. Transient stability of a power system has been gained considerable attention from researchers due to its importance. The FACTs devices that provide opportunities to control the power and damping oscillations are used. Therefore, this paper sheds light on the modified particle swarm optimization (M-PSO) algorithm is used such in the paper to discover the design optimal the Proportional Integral controller (PI-C) parameters that improve the stability the Multi-Machine Power System (MMPS) with Unified Power Flow Controller (UPFC). Performance the power system under event of fault is investigating by utilizes the proposed two strategies to simulate the operational characteristics of power system by the UPFC using: first, the conventional (PI-C) based on Particle Swarm Optimization (PI-C-PSO); secondly, (PI-C) based on modified Particle Swarm Optimization (PI-C-M-PSO) algorithm. The simulation results show the behavior of power system with and without UPFC, that the proposed (PI-C-M-PSO) technicality has enhanced response the system compared for other techniques, that since it gives undershoot and over-shoot previously existence minimized in the transitions, it has a ripple lower. Matlab package has been employed to implement this study. The simulation results show that the transient stability of the respective system enhanced considerably with this technique.</span>

scholarly journals An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 357 ◽  
Author(s):  
Shu-Kai S. Fan ◽  
Chih-Hung Jen
Keyword(s):  
Particle Swarm Optimization ◽  
Unconstrained Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Particle Swarm Optimizer ◽  
Swarm Optimization ◽  
Searching Strategy ◽  
Wide Range

Particle swarm optimization (PSO) is a population-based optimization technique that has been applied extensively to a wide range of engineering problems. This paper proposes a variation of the original PSO algorithm for unconstrained optimization, dubbed the enhanced partial search particle swarm optimizer (EPS-PSO), using the idea of cooperative multiple swarms in an attempt to improve the convergence and efficiency of the original PSO algorithm. The cooperative searching strategy is particularly devised to prevent the particles from being trapped into the local optimal solutions and tries to locate the global optimal solution efficiently. The effectiveness of the proposed algorithm is verified through the simulation study where the EPS-PSO algorithm is compared to a variety of exiting “cooperative” PSO algorithms in terms of noted benchmark functions.

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