Solution of Unit Commitment Problem Using Enhanced Genetic Algorithm

被引：0
|
作者：
Singhal, Prateek K. [1 ]
Naresh, R. [1 ]
Sharma, Veena [1 ]
Kumar, Goutham N. [1 ]
机构：
[1] Natl Inst Technol, Dept Elect Engn, Hamirpur 177005, Himachal Prades, India
来源：
2014 EIGHTEENTH NATIONAL POWER SYSTEMS CONFERENCE (NPSC) | 2014年
关键词：
economic dispatch; genetic algorithm; unit commitment;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, enhanced genetic algorithm (EGA) is used to solve the short-term unit commitment problem (UCP) and the enhanced lambda iteration (ELI) method is used to solve the economic dispatch (ED) sub-problem. Based on EGA, the problem specific operators have been integrated in the simple GA algorithm and thus, enhanced the quality of the solution. Performance of EGA is tested on 2 test systems comprising of 4unit and 10-unit over the scheduling time horizon of 8 hours and 24 hours respectively. Results demonstrate that the proposed method is superior to the other reported methods in the literature.
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页数：6
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