Please use this identifier to cite or link to this item:
http://dspace2020.uniten.edu.my:8080/handle/123456789/21461| Title: | Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system | Authors: | Abas N.A.S. Musirin I. Jelani S. Mansor M.H. Honnoon N.M.S. Othman M.M. #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# |
Issue Date: | 2019 | Abstract: | This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system. © 2019 Institute of Advanced Engineering and Science. All rights reserved. | URI: | http://dspace2020.uniten.edu.my:8080/handle/123456789/21461 |
| Appears in Collections: | UNITEN Ebook and Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system.pdf | 584.57 kB | Adobe PDF | View/Open |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.