Universiti Teknologi Malaysia Institutional Repository

Implementing modified particle swarm optimization method to solve economic load dispatch problem

Zaraki, Abolfazl (2009) Implementing modified particle swarm optimization method to solve economic load dispatch problem. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

[img]
Preview
PDF
227kB

Abstract

Economic Load Dispatch (ELD) is one of the important optimization tasks which provide an economic condition for power systems. In this work, Modified Particle Swarm Optimization (PSO) as an efficient and reliable evolutionary based approach has been proposed to solve the constraint economic load dispatch problem. The proposed method is able to determine, output power generation for all of the power generation units, so that the total, constraint cost function is minimized. In project report, a piecewise quadratic function is used to represent the fuel cost of each generation units, and the B-coefficient method is used to model transmission losses. The feasibility of the proposed Modified PSO is demonstrated for 4 power system test cases, consisting 3,6,15, and 40 generation units. The obtained Modified PSO results are compared with Standard PSO (SPSO), Genetic Algorithm (GA) and Quadratic Programming (QP) base approaches. These results reveal that the proposed method is capable to get higher quality solution including mathematical simplicity, fast convergence, and robustness to solve hard economic load dispatch problem.

Item Type:Thesis (Masters)
Additional Information:Supervisor : Dr. Mohd. Fauzi Othman; Thesis (Sarjana Kejuruteraan (Elektrik - Mekatronik dan Kawalan Automatik)) - Universiti Teknologi Malaysia, 2009
Uncontrolled Keywords:mathematical optimization, swarm intelligence
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:18344
Deposited By: Kamariah Mohamed Jong
Deposited On:11 Oct 2013 01:25
Last Modified:20 Sep 2017 06:52

Repository Staff Only: item control page