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http://ir.futminna.edu.ng:8080/jspui/handle/123456789/9481| Title: | A Comparative Study on Implementation of Genetic Algorithm (GA) and ATC to Generator Siting in Nigerian 330kV Power Network |
| Authors: | Sadiq, A. A. Nwohu, M. N. Ambafi, J. G. |
| Keywords: | Generator Siting Genetic Algorithm (GA) Available Transfer Capability (ATC) Power Network Power loss |
| Issue Date: | 2013 |
| Publisher: | TI Journals, International Journal of Engineering Sciences |
| Citation: | A. A. Sadiq, M. N. Nwohu and J. G. Ambafi (2013). A Comparative Study on Implementation of Genetic Algorithm (GA) and ATC to Generator Siting in Nigerian 330kV Power Network. TI Journals, International Journal of Engineering Sciences Vol. 2, No. 8, Pp 350-360. |
| Series/Report no.: | Vol. 2, No. 8,;Pp 350-360. |
| Abstract: | As the Nigerian electricity market tends towards deregulation thereby encouraging Independent Power Producers (IPP), one key issue is the optimal location of their generating units for a given network. In this paper, the application of Available Transfer Capability (ATC) expected values among selected candidate buses is used as criterion to siting of new generator. However, Genetic algorithm (GA) approach is employed to locate the optimal bus for siting a new generation resource and a comparison between the use of ATC level index and GA is made. The results shows that the use of genetic algorithm for real power loss minimization is a better technique for optimal generator siting when compared with ATC level index. |
| Description: | Genetic algorithm (GA) approach is employed to locate the optimal bus for siting a new generation resource and a comparison between the use of ATC level index and GA is made. |
| URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/9481 |
| Appears in Collections: | Electrical/Electronic Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 51f500d88cd935.37732514(2).pdf | 476.43 kB | Adobe PDF | View/Open |
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