Forecast analysis of hybrid renewable energies using deep learning: A case study with data from the Capricorn FLX 202004 weather station in Biskra, Algeria-Reference-Cited by-同舟云学术

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Forecast analysis of hybrid renewable energies using deep learning: A case study with data from the Capricorn FLX 202004 weather station in Biskra, Algeria

Published:2024-04-21 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 8th International Conference on Image and Signal Processing and their Applications (ISPA)
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Author:

Badis Bacha¹,Ghodbane Hatem¹,Dahmani Habiba²,Ferhat Zeyd³,Riyadh Barka³,Betka Abir⁴,Selma Boutiba¹,Kahhoul Zineddine¹,Lakhdar Tiar Mohamed¹

Affiliation:

1. University of Biskra,Electrical Engineering Department,Biskra,Algeria

2. University of M’sila, Algeria,Electrical Engineering Department,Msila,Algeria

3. University of M’sila, Algeria,Departement of Electronics,Msila,Algeria

4. University of El-Oued, Algeria,Electrical Engineering Department,El-Oued,Algeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10536721/10536698/10536766.pdf?arnumber=10536766

Reference26 articles.

1. Climate change: The game changer in the Gulf Cooperation Council Region

2. Weather data errors analysis in solar power stations generation forecasting

3. Weather station selection for electric load forecasting

4. Application of Artificial Intelligence Methods for Hybrid Energy System Optimization

5. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

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