DocumentCode
518525
Title
Notice of Retraction
Environmental/Economic Dispatch using a improved Differential Evolution
Author
Libiao Zhang ; Xiangli Xu ; Sujing Wang ; Chunguang Zhou ; Caitang Sun
Author_Institution
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Volume
4
fYear
2010
fDate
16-18 April 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem based on Differential Evolution (DE). The proposed algorithm is different from the classical DE in the process of mutation. The mutation is carried out with three vectors; one is the local best, other is the global best and third one is selected as randomly. The improved mutation operation is more explicit directional than classic ED, and it push the trial vector quickly towards the global optima. It effectively guarantees the convergence of the algorithm and the diversity solutions. On this basis, a new multiobjective evolutionary algorithm is proposed to handle the EED. The performance of algorithm has been examined over the standard IEEE 30 bus six generator test system, and other multi-objective evolutionary algorithm are compared. Testing and comparing results showed the effectiveness of the algorithm.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem based on Differential Evolution (DE). The proposed algorithm is different from the classical DE in the process of mutation. The mutation is carried out with three vectors; one is the local best, other is the global best and third one is selected as randomly. The improved mutation operation is more explicit directional than classic ED, and it push the trial vector quickly towards the global optima. It effectively guarantees the convergence of the algorithm and the diversity solutions. On this basis, a new multiobjective evolutionary algorithm is proposed to handle the EED. The performance of algorithm has been examined over the standard IEEE 30 bus six generator test system, and other multi-objective evolutionary algorithm are compared. Testing and comparing results showed the effectiveness of the algorithm.
Keywords
evolutionary computation; power generation dispatch; power generation economics; diversity solutions; economic dispatch; environmental dispatch; global best; global optima; improved differential evolution; local best; multiobjective evolutionary algorithm; mutation operation; standard IEEE 30 bus six generator test system; trial vector; Computer science; Cost function; Educational institutions; Environmental economics; Evolutionary computation; Fuel economy; Genetic algorithms; Genetic mutations; Power generation economics; Sun; differential evolution; environmental/economic dispatch; multiobjective evolutionary;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5486369
Filename
5486369
Link To Document