Pheromone-sharing Mechanism Particle Swarm Optimization for Restoring Solutions in Electric Power Systems

2012 ◽  
Vol 4 (7) ◽  
pp. 291-298 ◽  
Author(s):  
Xiaodong SHEN ◽  
Junyong LIU ◽  
Yan LIU
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Electric Power ◽  
Particle Swarm ◽  
Electric Power Systems ◽  
Swarm Optimization

scholarly journals Implementation of Particle Swarm Optimization (PSO) Algorithm for Tuning of Power System Stabilizers in Multimachine Electric Power Systems

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2093 ◽  
Author(s):  
Humberto Verdejo ◽  
Victor Pino ◽  
Wolfgang Kliemann ◽  
Cristhian Becker ◽  
José Delpiano
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Particle Swarm ◽  
Electric Power Systems ◽  
Simulation Software ◽  
Power System Stabilizers ◽  
Swarm Optimization ◽  
Wide Range

The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.

scholarly journals A Novel Application of Improved Marine Predators Algorithm and Particle Swarm Optimization for Solving the ORPD Problem

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5679
Author(s):  
Mohamed A. M. Shaheen ◽  
Dalia Yousri ◽  
Ahmed Fathy ◽  
Hany M. Hasanien ◽  
Abdulaziz Alkuhayli ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Electric Power ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Reactive Power ◽  
Particle Swarm ◽  
Continuous Optimization ◽  
Swarm Optimization ◽  
Marine Predators

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.

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