A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch

2011 ◽  
Vol 33 (1) ◽  
pp. 115-123 ◽  
Author(s):  
Rajesh Kumar ◽  
Devendra Sharma ◽  
Abhinav Sadu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Economic Power ◽  
Swarm Optimization ◽  
Agent Based ◽  
Power Dispatch ◽  
Multi Agent ◽  
Economic Power Dispatch

scholarly journals Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm for Solving Optimal Reactive Power Dispatch Problem

2020 ◽  
Vol 3 (1) ◽  
pp. 12-21
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Symbiotic Organisms Search ◽  
Power Dispatch ◽  
Fitness Value ◽  
Symbiotic Organisms

In this work Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm (HGPSOS) has been done for solving the power dispatch problem. Genetic particle swarm optimization problem has been hybridized with Symbiotic organisms search (SOS) algorithm to solve the problem. Genetic particle swarm optimization algorithm is formed by combining the Particle swarm optimization algorithm (PSO) with genetic algorithm (GA).  Symbiotic organisms search algorithm is based on the actions between two different organisms in the ecosystem- mutualism, commensalism and parasitism. Exploration process has been instigated capriciously and every organism specifies a solution with fitness value.  Projected HGPSOS algorithm improves the quality of the search.  Proposed HGPSOS algorithm is tested in IEEE 30, bus test system- power loss minimization, voltage deviation minimization and voltage stability enhancement has been attained.

A Novel Hybrid Optimization Algorithm Based on Multi-Agent and Particle Swarm

2011 ◽  
Vol 460-461 ◽  
pp. 512-517
Author(s):  
De Jia Shi ◽  
Wei Jin Jiang ◽  
Xiao Ling Ding
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Agent Interactions ◽  
Fitness Value ◽  
Multi Agent

A novel multi-agent particle swarm optimization algorithm (MAI'SO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in MAI.SO represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to decrease fitness value, quickly, agents compete and cooperate with their neighbors. and they can also use knowledge. Making use of these agent interactions and evolution mechanism of I.SO. MAPSO realizes the purpose of' minimizing the value of' objective function. MAPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. It is shown that the proposed approach converges to better solutions much faster than the earlier reported approaches

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