A hybrid particle swarm optimization and pattern search method to solve the economic load dispatch problem

Labbi, Yacine; Attous, D. Ben

doi:10.1007/s13198-013-0186-1

Cited by 15 publications

(13 citation statements)

References 13 publications

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“…nonlinear function. The method is highly competitive for its better general convergence performance [66]. Ahmed Saber presents modified particle swarm optimization, which includes advantages of bacterial foraging (BF) and PSO for constrained dynamic economic dispatch (ED) problem.…”

Section: Ismail Ziane Et Al Provide Multi-objective Simulatedmentioning

confidence: 99%

Optimization techniques for economic load dispatch problem in power plant

2021

SUDORJ

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This paper presents survey of optimization techniques used to solve the problem of economic load dispatch in power stations. Since there is no single method available for solving all economic dispatch problems efficiently, thus a number of different optimization methods have been developed to solve this problem. These techniques were divided into three types depending on the efficiency of the solution: stochastic process techniques, statistical methods, and mathematical programming techniques which divided to local optimization, and global optimization. It is found that is better to use hybrid techniques to overcome load dispatch problems so as to achieve significant improvements in computation time, convergence properties, solution quality, or parameter robustness.

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Section: Ismail Ziane Et Al Provide Multi-objective Simulatedmentioning

confidence: 99%

Optimization techniques for economic load dispatch problem in power plant

2021

SUDORJ

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“…The six unit test system chosen in this thesis is the IEEE 30 bus system [17] in which cost coefficients of the generating units, generating capacity of each are specified. The test system comprises of 6 generators, 41 transmission lines and 30 buses.…”

Section: Test Casementioning

confidence: 99%

Optimal Scheduling Of Generation Using ANFIS

Sobhanbabu¹,

Manohar²,

Reddy³

2017

IJERA

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This paper proposes application of PSO trained Anfis for solving optimal scheduling of generation. Particle swarm optimization (PSO) is a population based stochastic optimization technique, inspired by social behaviour of bird flocking or fish schooling. The proposed approach has been examined and tested with the numerical results of optimal scheduling of generation with three and six generating units. The results of the proposed PSO-ANFIS algorithm are compared with that of other techniques such as Lambda-Iteration Method and PSO Method and compared to both cases; the proposed algorithm outperforms the solution.

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“…PS is another optimization technique [31] and has been shown to have superior performance even compared with PSO for both simple and complicated problems [32]. In addition, unlike GA and PSO, PS can adapt to global and local search [33] and requires very few hand-tuned input parameters. These parameters can affect the performance significantly, particularly in both conventional and improved versions of GA [34].…”

Section: Problem Formulation Of Collaborative Multiband Sensingmentioning

confidence: 99%

Pattern-Search-Based Nonconvex Cooperative Sensing in Multiband Cognitive Radio Systems

Khwaja

Naeem

Anpalagan

2016

IEEE Systems Journal

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In this paper, a pattern search (PS)-based solution is proposed for nonconvex multiband cooperative sensing (NCMCS) problem in cognitive radio systems. This problem consists of maximizing cumulative throughput subject to constraints on cumulative interference, probability of detection, and probability of false alarm. Initially in existing literature, this problem was solved under constraints that make it convex. However, removing the conditions for convexity and solving the NCMCS problem have been shown to improve performance. A two-step PS-based solution is presented: The first step uses uniformly distributed random sets of input points to find a solution. The set of points that gives the maximum throughput is chosen as input to the PS algorithm. Numerical examples show the improvement of the proposed method over existing genetic-algorithm-based solution, as well as PS-algorithm-based solution that uses a single set of random points as inputs. The proposed two-step solution gives higher cumulative throughput and is not sensitive to the choice of input, unlike the PS-based solution using a single set of random points as input.

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A hybrid particle swarm optimization and pattern search method to solve the economic load dispatch problem

Cited by 15 publications

References 13 publications

Optimization techniques for economic load dispatch problem in power plant

Optimization techniques for economic load dispatch problem in power plant

Optimal Scheduling Of Generation Using ANFIS

Pattern-Search-Based Nonconvex Cooperative Sensing in Multiband Cognitive Radio Systems

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