Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/34683| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dimishkovska Krsteski, Natasha | en_US |
| dc.contributor.author | Iliev, Atanas | en_US |
| dc.date.accessioned | 2026-01-28T10:51:40Z | - |
| dc.date.available | 2026-01-28T10:51:40Z | - |
| dc.date.issued | 2024-09-01 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.12188/34683 | - |
| dc.description.abstract | <jats:p>This paper introduces a modification of the genetic algorithm aimed at enhancing the selection process for reproducing the next generation. This modification accelerates the optimization process and improves the outcome. The case study analyzes a grid-connected microgrid comprising renewable energy sources, a battery storage system, prosumers with installed photovoltaic generators, and consumers. The effectiveness of the proposed modification is validated through comparison with two selection algorithms commonly used in the standard genetic algorithms.</jats:p> | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | International Journal on Information Technologies and Security | en_US |
| dc.relation.ispartof | International Journal on Information Technologies and Security | en_US |
| dc.title | Modified genetic algorithm for unit commitment of grid connected microgrids under real time pricing conditions | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | 10.59035/hhvg2870 | - |
| dc.identifier.url | https://ijits-bg.com/sites/default/files/archive/2024%28vol.16%29/No3/contents/2024-N3-08.pdf | - |
| dc.identifier.volume | 16 | - |
| dc.identifier.issue | 3 | - |
| dc.identifier.fpage | 81 | - |
| dc.identifier.lpage | 90 | - |
| item.fulltext | With Fulltext | - |
| item.grantfulltext | open | - |
| crisitem.author.dept | Faculty of Electrical Engineering and Information Technologies | - |
| crisitem.author.dept | Faculty of Electrical Engineering and Information Technologies | - |
| Appears in Collections: | Faculty of Electrical Engineering and Information Technologies: Journal Articles | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| 2024-N3-08.pdf | 429.6 kB | Adobe PDF | View/Open |
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