scholarly journals Quantum-behaved Particle Swarm Optimization for Power Economic Dispatch Problem of Units with Multiple Fuel Option

2017 ◽  
Vol 2 (12) ◽  
pp. 11 ◽  
Author(s):  
Chao Lung Chiang
Keyword(s):  
Particle Swarm Optimization ◽  
Lagrange Function ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Fuel Price ◽  
Swarm Optimization ◽  
Size Population ◽  
Economic Dispatch Problem ◽  
Power Economic

This paper presents a quantum-behaved particle swarm optimization (QPSO) with a multiple updating (MU) for solving the power economic dispatch problem (PEDP) of generators with multiple fuel options (MFOs). The QPSO assists the proposed method efficaciously find and precisely search. The MU helps the proposed method prevent deforming the augmented Lagrange function (ALF) and caused difficultly in searching optimal solution. The proposed approach combines the QPSO and the MU that has benefits of adopting a widespread area of punishment parameters and a small-size population. The proposed algorithm has been demonstrated on a practical ten generating units system; every one unit is composed of two or three fuel changes. The entire fuel price got by the proposed QPSO-MU has been competed with former studies for validating its efficacy. Compared achievements clearly express that the presented method is an effective alternative for resolving PEDP of units with MFOs in the realistic operations of power system.

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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