Intelligent learning approaches for renewable and sustainable energy:
Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. Sections introdu...
Gespeichert in:
| Weitere Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Elsevier
[2024]
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| Schlagworte: | |
| Zusammenfassung: | Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. Sections introduce intelligent learning approaches and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. Other sections provide detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, optimization, and more. This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence |
| Beschreibung: | Section I: Introduction to intelligent learning approaches for renewable and sustainable energy ; 1. Artificial Intelligence-based sustainability in energy ; 2. Machine-learning-based sustainability in energy ; 3. Transforming the grid: AI, ML, Renewable, Storage, EVs, and Prosumers ; 4. Role of intelligent techniques in large-scale integration of renewable energy ; 5. Variability of renewable energy generation and flexibility initiatives ; Section II: Applications of intelligence learning approaches for renewable and sustainable energy ; 6. Intelligent learning models for renewable energy forecasting ; 7. Intelligent learning models for balancing supply and demand ; 8. Intelligent learning analysis for a flexibility energy approach towards renewable energy integration ; 9. Intelligent learning analysis for energy management ; 10. Intelligent learning approaches for demand-side controller for BIPVs integrated buildings ; 11. Intelligent learning approaches for single and multi-objective optimization methodology ; 12. Intelligent learning approaches for optimization of integrated energy systems |
| Beschreibung: | xiv, 299 Seiten Illustrationen, Diagramme 450 gr |
| ISBN: | 9780443158063 |
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| 500 | |a Section I: Introduction to intelligent learning approaches for renewable and sustainable energy ; 1. Artificial Intelligence-based sustainability in energy ; 2. Machine-learning-based sustainability in energy ; 3. Transforming the grid: AI, ML, Renewable, Storage, EVs, and Prosumers ; 4. Role of intelligent techniques in large-scale integration of renewable energy ; 5. Variability of renewable energy generation and flexibility initiatives ; Section II: Applications of intelligence learning approaches for renewable and sustainable energy ; 6. Intelligent learning models for renewable energy forecasting ; 7. Intelligent learning models for balancing supply and demand ; 8. Intelligent learning analysis for a flexibility energy approach towards renewable energy integration ; 9. Intelligent learning analysis for energy management ; 10. Intelligent learning approaches for demand-side controller for BIPVs integrated buildings ; 11. Intelligent learning approaches for single and multi-objective optimization methodology ; 12. Intelligent learning approaches for optimization of integrated energy systems | ||
| 520 | |a Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. Sections introduce intelligent learning approaches and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. Other sections provide detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, optimization, and more. This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence | ||
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| index_date | 2024-07-03T23:23:19Z |
| indexdate | 2024-07-10T10:09:22Z |
| institution | BVB |
| isbn | 9780443158063 |
| language | English |
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| physical | xiv, 299 Seiten Illustrationen, Diagramme 450 gr |
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| spelling | Intelligent learning approaches for renewable and sustainable energy edited by Josep M. Guerrero [und 3 weitere] Amsterdam Elsevier [2024] xiv, 299 Seiten Illustrationen, Diagramme 450 gr txt rdacontent n rdamedia nc rdacarrier Section I: Introduction to intelligent learning approaches for renewable and sustainable energy ; 1. Artificial Intelligence-based sustainability in energy ; 2. Machine-learning-based sustainability in energy ; 3. Transforming the grid: AI, ML, Renewable, Storage, EVs, and Prosumers ; 4. Role of intelligent techniques in large-scale integration of renewable energy ; 5. Variability of renewable energy generation and flexibility initiatives ; Section II: Applications of intelligence learning approaches for renewable and sustainable energy ; 6. Intelligent learning models for renewable energy forecasting ; 7. Intelligent learning models for balancing supply and demand ; 8. Intelligent learning analysis for a flexibility energy approach towards renewable energy integration ; 9. Intelligent learning analysis for energy management ; 10. Intelligent learning approaches for demand-side controller for BIPVs integrated buildings ; 11. Intelligent learning approaches for single and multi-objective optimization methodology ; 12. Intelligent learning approaches for optimization of integrated energy systems Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. Sections introduce intelligent learning approaches and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. Other sections provide detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, optimization, and more. This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence bicssc bisacsh Guerrero, Josep M. (DE-588)1225427533 edt |
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| title | Intelligent learning approaches for renewable and sustainable energy |
| title_auth | Intelligent learning approaches for renewable and sustainable energy |
| title_exact_search | Intelligent learning approaches for renewable and sustainable energy |
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| title_full | Intelligent learning approaches for renewable and sustainable energy edited by Josep M. Guerrero [und 3 weitere] |
| title_fullStr | Intelligent learning approaches for renewable and sustainable energy edited by Josep M. Guerrero [und 3 weitere] |
| title_full_unstemmed | Intelligent learning approaches for renewable and sustainable energy edited by Josep M. Guerrero [und 3 weitere] |
| title_short | Intelligent learning approaches for renewable and sustainable energy |
| title_sort | intelligent learning approaches for renewable and sustainable energy |
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