Multi-Leader Comprehensive Learning Particle Swarm Optimization with Adaptive Mutation for Economic Load Dispatch Problems
نویسندگان
چکیده
منابع مشابه
Economic Load Dispatch Using Particle Swarm Optimization
Volume 2, Issue 4, April 2013 Page 476 Abstract Economic load dispatch is a non linear optimization problem which is of great importance in power systems. While analytical methods suffer from slow convergence and curse of dimensionality particle swarm optimization can be an efficient alternative to solve large scale non linear optimization problems. This paper presents an overview of basic PSO ...
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Particle swarm optimization (PSO ) is an effective & reliable evolutionary based approach .Due to its higher quality solution including mathematical simplicity, fast convergence & robustness it has become popular for many optimization problems. There are various field of power system in which PSO is successfully applied. Economic Load Dispatch(ELD) is one of important tasks which provide an eco...
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This work deals with the optimization of power flow through interconnected system. The work deals with efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with line flows and voltage constraints. The work employs PSO algorithm for ELD. PSO is a robust, stochastic computational technique based on movement and intelligence of swarm. The work introduces a c...
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Economic load dispatch (ELD) problem is a common task in the operational planning of a power system, which requires to be optimized. This paper presents an effective and reliable particle swarm optimization (PSO) technique for the economic load dispatch problem. The results have been demonstrated for ELD of standard 3-generator and 6-generator systems with and without consideration of transmiss...
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A new versatile optimization, the particle swarm optimization based on multi-agent system (MAPSO) is presented. The economic load dispatch (ELD) problem of power system can be solved by the algorithm. By competing and cooperating with the randomly selected neighbors, and adjusting its global searching ability and local exploring ability, this algorithm achieves the goal of high convergence prec...
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ژورنال
عنوان ژورنال: Energies
سال: 2018
ISSN: 1996-1073
DOI: 10.3390/en12010116