Adaptive particle swarm optimisation for solving non-convex economic dispatch problems

Nurhafizah Jamain, Ismail Musirin, Mohd Helmi Mansor, Muhammad Murtadha Othman, Siti Aliyah Mohd Salleh

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.

Original languageEnglish
Pages (from-to)275-286
Number of pages12
JournalPertanika Journal of Science and Technology
Volume25
Issue numberS3
Publication statusPublished - 01 Mar 2017

Fingerprint

swarms
Particle swarm optimization (PSO)
Economics
economics
methodology
particle
case studies

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Chemical Engineering(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

Jamain, Nurhafizah ; Musirin, Ismail ; Mansor, Mohd Helmi ; Othman, Muhammad Murtadha ; Salleh, Siti Aliyah Mohd. / Adaptive particle swarm optimisation for solving non-convex economic dispatch problems. In: Pertanika Journal of Science and Technology. 2017 ; Vol. 25, No. S3. pp. 275-286.
@article{2ccc5ecc31c24380b1eab0a31cf5f74c,
title = "Adaptive particle swarm optimisation for solving non-convex economic dispatch problems",
abstract = "This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.",
author = "Nurhafizah Jamain and Ismail Musirin and Mansor, {Mohd Helmi} and Othman, {Muhammad Murtadha} and Salleh, {Siti Aliyah Mohd}",
year = "2017",
month = "3",
day = "1",
language = "English",
volume = "25",
pages = "275--286",
journal = "Pertanika Journal of Science and Technology",
issn = "0128-7680",
publisher = "Universiti Putra Malaysia",
number = "S3",

}

Adaptive particle swarm optimisation for solving non-convex economic dispatch problems. / Jamain, Nurhafizah; Musirin, Ismail; Mansor, Mohd Helmi; Othman, Muhammad Murtadha; Salleh, Siti Aliyah Mohd.

In: Pertanika Journal of Science and Technology, Vol. 25, No. S3, 01.03.2017, p. 275-286.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Adaptive particle swarm optimisation for solving non-convex economic dispatch problems

AU - Jamain, Nurhafizah

AU - Musirin, Ismail

AU - Mansor, Mohd Helmi

AU - Othman, Muhammad Murtadha

AU - Salleh, Siti Aliyah Mohd

PY - 2017/3/1

Y1 - 2017/3/1

N2 - This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.

AB - This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.

UR - http://www.scopus.com/inward/record.url?scp=85049130525&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049130525&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85049130525

VL - 25

SP - 275

EP - 286

JO - Pertanika Journal of Science and Technology

JF - Pertanika Journal of Science and Technology

SN - 0128-7680

IS - S3

ER -