Estimation of fuel cost curve parameters for thermal power plants using the ABC algorithm

Yusuf SÖNMEZ

Article Details

Estimation of fuel cost curve parameters for thermal power plants using the ABC algorithm

Authors:

Yusuf SÖNMEZ

Publisher:

TUBITAK

Journal:

Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.1827-1841

Document Type:

Article

Publication Date:

11/2012

Document Language:

Turkish

Document ID (Org No.):

2000743455

Frequency:

Bimonthly

eISSN:

1303-6203

pISSN:

1300-0632

Abstract:

 

The solution accuracy of economic dispatch problems is associated with the  accuracy of the fuel cost curve parameters. Therefore, updating of these  parameters is a very important issue to further improve the final accuracy  of economic dispatch problems. Estimating the parameters of the fuel cost  curve may be the best solution for this issue. This paper presents an  application of the artificial bee colony (ABC) algorithm to estimate the  fuel cost curve parameters of thermal power plants. In the estimation  problem, 1st-, 2nd-, and 3rd-order fuel cost functions are used, and the  estimation problem is formulated as an optimization one. The ABC algorithm  is used to solve this optimization problem by minimizing the total error in  the estimated parameters. In this study, in order to evaluate the  performance of the ABC algorithm, it is tested on 3 different cases that  have 3 different fuel cost types, such as coal, oil, and gas. The results  obtained from the proposed method are compared with the genetic algorithm,  particle swarm optimization, and least square error methods reported  previously in the literature. The results show that the ABC algorithm is  stronger than the others at solving such a problem.

 

The solution accuracy of economic dispatch problems is associated with the  accuracy of the fuel cost curve parameters. Therefore, updating of these  parameters is a very important issue to further improve the final accuracy  of economic dispatch problems. Estimating the parameters of the fuel cost  curve may be the best solution for this issue. This paper presents an  application of the artificial bee colony (ABC) algorithm to estimate the  fuel cost curve parameters of thermal power plants. In the estimation  problem, 1st-, 2nd-, and 3rd-order fuel cost functions are used, and the  estimation problem is formulated as an optimization one. The ABC algorithm  is used to solve this optimization problem by minimizing the total error in  the estimated parameters. In this study, in order to evaluate the  performance of the ABC algorithm, it is tested on 3 different cases that  have 3 different fuel cost types, such as coal, oil, and gas. The results  obtained from the proposed method are compared with the genetic algorithm,  particle swarm optimization, and least square error methods reported  previously in the literature. The results show that the ABC algorithm is  stronger than the others at solving such a problem.

Article Details

Estimation of fuel cost curve parameters for thermal power plants using the ABC algorithm

Authors: Yusuf SÖNMEZ

Publisher: TUBITAK

Journal: Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.1827-1841

Document Type: Article

Publication Date: 11/2012

Document Language: Turkish

Document ID (Org No.): 2000743455

Frequency: Bimonthly

eISSN: 1303-6203

pISSN: 1300-0632

Issues

Authors:

Yusuf SÖNMEZ

Publisher:

TUBITAK

Journal:

Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.1827-1841

Document Type:

Article

Publication Date:

11/2012

Document Language:

Turkish

Document ID (Org No.):

2000743455

Frequency:

Bimonthly

eISSN:

1303-6203

pISSN:

1300-0632