Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch

2008 ◽  
Vol 23 (3) ◽  
pp. 1079-1087 ◽  
Author(s):  
K.T. Chaturvedi ◽  
M. Pandit ◽  
L. Srivastava
Keyword(s):  
Particle Swarm Optimization ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Self Organizing

A New Improved Particle Swarm Optimization for Solving Nonconvex Economic Dispatch Problems

2013 ◽  
Vol 2 (1) ◽  
pp. 60-77 ◽  
Author(s):  
Jirawadee Polprasert ◽  
Weerakorn Ongsakul ◽  
Vo Ngoc Dieu
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Search Space ◽  
The Self ◽  
Particle Swarm Optimizer ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Self Organizing

This paper proposes a new improved particle swarm optimization (NIPSO) for solving nonconvex economic dispatch (ED) problem in power systems including multiple fuel options (MFO) and valve-point loading effects (VPLE). The proposed NIPSO method is based on the self-organizing hierarchical (SOH) particle swarm optimizer with time-varying acceleration coefficients (TVAC). The self-organizing hierarchical can handle the premature convergence of the problem by re-initialization of velocity whenever particles are stagnated in the search space. During the optimization process, the performance of TVAC is applied for properly controlling both local and global explorations with cognitive component and social component of the swarm to obtain the optimum solution accurately and efficiently. The proposed NIPSO algorithm is tested in different types of non-smooth cost functions for solving ED problems and the obtained results are compared to those from many other methods in the literature. The results have revealed that the proposed NIPSO method is effective and feasible in finding higher quality solutions for non-smooth ED problems than many other methods.

scholarly journals Perbandingan Metode Gaussian Particle Swarm Optimization (GPSO) dan Lagrange Multiplier pada Masalah Economic Dispatch

2012 ◽  
Vol 3 (1) ◽  
pp. 228
Author(s):  
Siti Komsiyah
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Power ◽  
Lagrange Multiplier ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Economic Planning ◽  
Electric Power System ◽  
Planning Problem ◽  
Swarm Optimization ◽  
Economic Dispatch Problem

On electric power system operation, economic planning problem is one variable to take into account due to operational cost efficiency. Economic Dispatch problem of electric power generation is discussed in this study to manage the output division on several units based on the the required load demand, with minimum operating cost yet is able to satisfy equality and inequality constraint of all units and system. In this study the Economic Dispatch problem which has non linear cost function is solved using swarm intelligent method is Gaussian Particle Swarm Optimization (GPSO) and Lagrange Multiplier. GPSO is a population-based stochastic algorithms which their moving is inspired by swarm intelligent and probabilities theories. To analize its accuracy, the Economic Dispatch solution by GPSO method is compared with Lagrange Multiplier method. From the test result it is proved that GPSO method gives economic planning calculation better than Lagrange Multiplier does.

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