Unit commitment solution based on improved particle swarm optimization method
Joint Authors
Abbas, Ali Ibrahim
Abbud, Afanin Anwar
Source
Engineering and Technology Journal
Issue
Vol. 39, Issue 10 (31 Oct. 2021), pp.1601-1609, 9 p.
Publisher
Publication Date
2021-10-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Topics
Abstract EN
This paper presents an algorithm to solve the unit commitment problem using the intelligence technique based on improved Particle Swarm Optimization (IPSO) for establishing the optimal scheduling of the generating units in the electric power system with the lowest production cost during a specified time and subjected to all the constraints.
The minimum production cost is calculated based on using the Lambda Iteration method.
A conventional method was also used for solving the unit commitment problem using the Dynamic Programming method (DP).
The two methods were tested on the 14-bus IEEE test system and the results of both methods were compared with each other and with other references.
The comparison showed the effectiveness of the proposed method over other This paper presents an algorithm to solve the unit commitment problem using the intelligence technique based on improved Particle Swarm Optimization (IPSO) for establishing the optimal scheduling of the generating units in the electric power system with the lowest production cost during a specified time and subjected to all the constraints.
The minimum production cost is calculated based on using the Lambda Iteration method.
A conventional method was also used for solving the unit commitment problem using the Dynamic Programming method (DP).
The two methods were tested on the 14-bus IEEE test system and the results of both methods were compared with each other and with other references.
The comparison showed the effectiveness of the proposed method over other methods.
American Psychological Association (APA)
Abbas, Ali Ibrahim& Abbud, Afanin Anwar. 2021. Unit commitment solution based on improved particle swarm optimization method. Engineering and Technology Journal،Vol. 39, no. 10, pp.1601-1609.
https://search.emarefa.net/detail/BIM-1281508
Modern Language Association (MLA)
Abbas, Ali Ibrahim& Abbud, Afanin Anwar. Unit commitment solution based on improved particle swarm optimization method. Engineering and Technology Journal Vol. 39, no. 10 (2021), pp.1601-1609.
https://search.emarefa.net/detail/BIM-1281508
American Medical Association (AMA)
Abbas, Ali Ibrahim& Abbud, Afanin Anwar. Unit commitment solution based on improved particle swarm optimization method. Engineering and Technology Journal. 2021. Vol. 39, no. 10, pp.1601-1609.
https://search.emarefa.net/detail/BIM-1281508
Data Type
Journal Articles
Language
English
Notes
Includes appendix : p. 1608-1609
Record ID
BIM-1281508