Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari

This paper presents a technique to solve economic dispatch (ED) with piecewise quadratic cost function (PQCF) by using particle swarm optimization (PSO) technique. Traditionally, each generator is represented by a single cost function. However, it is more realistic to represent the cost function as...

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Main Author: Nahari, Mohamad Erzat
Format: Thesis
Language:English
Published: 2012
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Online Access:https://ir.uitm.edu.my/id/eprint/67086/2/67086.pdf
https://ir.uitm.edu.my/id/eprint/67086/
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spelling my.uitm.ir.670862023-01-05T03:58:15Z https://ir.uitm.edu.my/id/eprint/67086/ Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari Nahari, Mohamad Erzat Production of electric energy or power. Powerplants. Central stations Electric power distribution. Electric power transmission This paper presents a technique to solve economic dispatch (ED) with piecewise quadratic cost function (PQCF) by using particle swarm optimization (PSO) technique. Traditionally, each generator is represented by a single cost function. However, it is more realistic to represent the cost function as a piecewise quadratic function when deal with generation units that use multiple fuel sources. In this study, the proposed PSO technique was tested on 10 units system. The results obtained show that the proposed PSO method was indeed capable of obtaining the solutions of PQCF problems. 2012 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/67086/2/67086.pdf Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari. (2012) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Production of electric energy or power. Powerplants. Central stations
Electric power distribution. Electric power transmission
spellingShingle Production of electric energy or power. Powerplants. Central stations
Electric power distribution. Electric power transmission
Nahari, Mohamad Erzat
Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
description This paper presents a technique to solve economic dispatch (ED) with piecewise quadratic cost function (PQCF) by using particle swarm optimization (PSO) technique. Traditionally, each generator is represented by a single cost function. However, it is more realistic to represent the cost function as a piecewise quadratic function when deal with generation units that use multiple fuel sources. In this study, the proposed PSO technique was tested on 10 units system. The results obtained show that the proposed PSO method was indeed capable of obtaining the solutions of PQCF problems.
format Thesis
author Nahari, Mohamad Erzat
author_facet Nahari, Mohamad Erzat
author_sort Nahari, Mohamad Erzat
title Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
title_short Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
title_full Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
title_fullStr Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
title_full_unstemmed Economic dispatch with piecewise quadratic cost functions using particle swarm optimization / Mohamad Erzat Nahari
title_sort economic dispatch with piecewise quadratic cost functions using particle swarm optimization / mohamad erzat nahari
publishDate 2012
url https://ir.uitm.edu.my/id/eprint/67086/2/67086.pdf
https://ir.uitm.edu.my/id/eprint/67086/
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score 13.209306