Parameter Estimation for Composite Load Model Using a Hybrid Searching Method

2013 ◽  
Vol 284-287 ◽  
pp. 1094-1098
Author(s):  
Manuel Y. del Castillo ◽  
Hwa Chang Song ◽  
Byong Jun Lee
Keyword(s):  
Parameter Estimation ◽  
System Stability ◽  
Complex Method ◽  
Third Order ◽  
Swarm Optimization ◽  
Load Model ◽  
System Stability Analysis ◽  
Searching Method ◽  
Composite Load Model ◽  
Motor Model

This paper presents a method for parameter estimation of composite load model using a hybrid searching algorithm, which is performed by the combination of particle swarm optimization (PSO) and complex method. The method intends to enhance the ability of local searching around the solutions, also taking the advantage of global searching by PSO. The load model of interest, in this paper, is composed of a static model and the third order induction motor model, for power system stability analysis. The origin of the hybrid method is to further apply the complex method as a local search for better solutions, with the selected particles from the PSO procedure performed at PSO iteration.

scholarly journals Parameter Estimation for the Composite Load Model

2012 ◽  
Vol 2 (2) ◽  
pp. 215-218 ◽  
Author(s):  
Byoung-Ho Kim ◽  
Hongrae Kim ◽  
Byoungjun Lee
Keyword(s):  
Parameter Estimation ◽  
Load Model ◽  
Composite Load Model

Dynamic Load Model using PSO-Based Parameter Estimation

2011 ◽  
Vol 131 (7) ◽  
pp. 557-566 ◽  
Author(s):  
Hisao Taoka ◽  
Junya Matsuki ◽  
Michiya Tomoda ◽  
Yasuhiro Hayashi ◽  
Yoshio Yamagishi ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Dynamic Load ◽  
Load Model ◽  
Dynamic Load Model

scholarly journals A Modified NM-PSO Method for Parameter Estimation Problems of Models

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
An Liu ◽  
Erwie Zahara ◽  
Ming-Ta Yang
Keyword(s):  
Genetic Algorithm ◽  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Wide Range ◽  
Estimation Problems

Ordinary differential equations usefully describe the behavior of a wide range of dynamic physical systems. The particle swarm optimization (PSO) method has been considered an effective tool for solving the engineering optimization problems for ordinary differential equations. This paper proposes a modified hybrid Nelder-Mead simplex search and particle swarm optimization (M-NM-PSO) method for solving parameter estimation problems. The M-NM-PSO method improves the efficiency of the PSO method and the conventional NM-PSO method by rapid convergence and better objective function value. Studies are made for three well-known cases, and the solutions of the M-NM-PSO method are compared with those by other methods published in the literature. The results demonstrate that the proposed M-NM-PSO method yields better estimation results than those obtained by the genetic algorithm, the modified genetic algorithm (real-coded GA (RCGA)), the conventional particle swarm optimization (PSO) method, and the conventional NM-PSO method.

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