Unit commitment solution using an optimized genetic system

This paper presents an investigation into the application of an optimized Genetic Algorithm (GA) to solve the Thermal Unit Commitment (UC) problem. A Parallel structure was first developed to handle the infeasibility problem in a structured and improved GA which provides an effective search process...

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Main Authors: Abookazemi, Kaveh, Ahmad, Hussein, Tavakolpour, Alireza, Hassan, Mohammad Yusri
Format: Article
Published: Elsevier Ltd. 2011
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Online Access:http://eprints.utm.my/id/eprint/29906/
http://dx.doi.org/10.1016/j.ijepes.2011.01.009
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spelling my.utm.299062020-10-30T05:13:29Z http://eprints.utm.my/id/eprint/29906/ Unit commitment solution using an optimized genetic system Abookazemi, Kaveh Ahmad, Hussein Tavakolpour, Alireza Hassan, Mohammad Yusri TK Electrical engineering. Electronics Nuclear engineering This paper presents an investigation into the application of an optimized Genetic Algorithm (GA) to solve the Thermal Unit Commitment (UC) problem. A Parallel structure was first developed to handle the infeasibility problem in a structured and improved GA which provides an effective search process and therefore greater economy. The proposed methodology resulted in a better performance with faster operation by using both computational methods and classification of unit characteristics. Typical constraints such as system power balance, minimum up and down times, start-up and shut-down ramps, have also been considered. A number of important parameters (standard and new parameters) of the UC problem have been identified. The proposed method is implemented and tested using a C# program. The tests are carried out using two systems including 10 and 20 units during a scheduling period of 24 h. The results are finally compared with those obtained from genetic schemes in other similar investigations through which the effectiveness of the proposed scheme is affirmed. Elsevier Ltd. 2011-05 Article PeerReviewed Abookazemi, Kaveh and Ahmad, Hussein and Tavakolpour, Alireza and Hassan, Mohammad Yusri (2011) Unit commitment solution using an optimized genetic system. International Journal of Electrical Power and Energy Systems, 33 (4). pp. 969-975. ISSN 0142-0615 http://dx.doi.org/10.1016/j.ijepes.2011.01.009 DOI:10.1016/j.ijepes.2011.01.009
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abookazemi, Kaveh
Ahmad, Hussein
Tavakolpour, Alireza
Hassan, Mohammad Yusri
Unit commitment solution using an optimized genetic system
description This paper presents an investigation into the application of an optimized Genetic Algorithm (GA) to solve the Thermal Unit Commitment (UC) problem. A Parallel structure was first developed to handle the infeasibility problem in a structured and improved GA which provides an effective search process and therefore greater economy. The proposed methodology resulted in a better performance with faster operation by using both computational methods and classification of unit characteristics. Typical constraints such as system power balance, minimum up and down times, start-up and shut-down ramps, have also been considered. A number of important parameters (standard and new parameters) of the UC problem have been identified. The proposed method is implemented and tested using a C# program. The tests are carried out using two systems including 10 and 20 units during a scheduling period of 24 h. The results are finally compared with those obtained from genetic schemes in other similar investigations through which the effectiveness of the proposed scheme is affirmed.
format Article
author Abookazemi, Kaveh
Ahmad, Hussein
Tavakolpour, Alireza
Hassan, Mohammad Yusri
author_facet Abookazemi, Kaveh
Ahmad, Hussein
Tavakolpour, Alireza
Hassan, Mohammad Yusri
author_sort Abookazemi, Kaveh
title Unit commitment solution using an optimized genetic system
title_short Unit commitment solution using an optimized genetic system
title_full Unit commitment solution using an optimized genetic system
title_fullStr Unit commitment solution using an optimized genetic system
title_full_unstemmed Unit commitment solution using an optimized genetic system
title_sort unit commitment solution using an optimized genetic system
publisher Elsevier Ltd.
publishDate 2011
url http://eprints.utm.my/id/eprint/29906/
http://dx.doi.org/10.1016/j.ijepes.2011.01.009
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