Feasibility analysis based on advanced deep learning techniques in integrating renewable energy resources into microgrids
Feasibility analysis based on advanced deep learning techniques in integrating renewable energy resources into microgrids
| dc.contributor.advisor | Çağlar, Ramazan | |
| dc.contributor.author | Fadoul, Fathi Farah | |
| dc.contributor.authorID | 504202026 | |
| dc.contributor.department | Electrical Engineering | |
| dc.date.accessioned | 2025-01-03T06:52:33Z | |
| dc.date.available | 2025-01-03T06:52:33Z | |
| dc.date.issued | 2024-07-17 | |
| dc.description | Thesis (Ph.D.) -- Istanbul Technical University, Graduate School, 2024 | |
| dc.description.degree | Ph.D. | |
| dc.identifier.uri | http://hdl.handle.net/11527/26092 | |
| dc.language.iso | en_US | |
| dc.publisher | Graduate School | |
| dc.sdg.type | Goal 4: Quality Education | |
| dc.sdg.type | Goal 7: Affordable and Clean Energy | |
| dc.subject | renewable energy | |
| dc.subject | yenilenebilir enerji | |
| dc.subject | microgrids | |
| dc.subject | mikroşebekeler | |
| dc.subject | deep learning | |
| dc.subject | derin öğrenme | |
| dc.title | Feasibility analysis based on advanced deep learning techniques in integrating renewable energy resources into microgrids | |
| dc.title.alternative | Yenilenebilir enerji kaynaklarının mikroşebekelere entegre edilmesinde gelişmiş derin öğrenme tekniklerine dayalı uygulanılabilirlik analizi | |
| dc.type | Doctoral Thesis |