Supervised evolutionary programming based technique for multi-DG installation in distribution system
Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming me...
| Published in: | IAES International Journal of Artificial Intelligence |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2020
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081034123&doi=10.11591%2fijai.v9.i1.pp11-17&partnerID=40&md5=e0d6842eb8ae63b7e2df4d991bce4f5f |
| Summary: | Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators. © 2020, Institute of Advanced Engineering and Science. All rights reserved. |
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| ISSN: | 20894872 |
| DOI: | 10.11591/ijai.v9.i1.pp11-17 |