AI and IOT in renewable energy
Intro -- Preface -- Contents -- Editors and Contributors -- 1 A Day-Ahead Power Output Forecasting of Three PV Systems Using Regression, Machine Learning and Deep Learning Techniques -- 1 Introduction -- 2 Description of Site and Data Preprocessing -- 3 Methodology -- 3.1 Gaussian Process Regression...
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| Weitere Verfasser: | , , , |
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Singapore
Springer
2021
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| Schriftenreihe: | Studies in infastructure and control
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| Schlagworte: | |
| Online Zugang: | Inhaltsverzeichnis |
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Tag hinzufügen | Zusammenfassung: | Intro -- Preface -- Contents -- Editors and Contributors -- 1 A Day-Ahead Power Output Forecasting of Three PV Systems Using Regression, Machine Learning and Deep Learning Techniques -- 1 Introduction -- 2 Description of Site and Data Preprocessing -- 3 Methodology -- 3.1 Gaussian Process Regression -- 3.2 Support Vector Regression (SVR) -- 3.3 Principal Component Analysis (PCA) -- 3.4 Deep Learning Technique (RNN-LSTM) -- 3.5 Performance Parameters to Measure Forecasting Accuracy -- 4 Results and Discussion -- 5 Conclusion -- References -- 2 Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization -- 1 Introduction -- 2 Latest Emerging Innovative Trends in Renewable Energy -- 2.1 Optimizing Offshore Wind in the U.S. -- 2.2 More Number of Electric Vehicles Running on Roads -- 2.3 Utilities and Corporations Investing in Solar Energy at Record Levels -- 2.4 Energy Efficiency Encouragement from Governments -- 2.5 Energy Storage Becoming a Significant Part of the Power Grid -- 3 IoT Applications Areas in Renewable Energy -- 3.1 Automation to Improve Overall Production -- 3.2 Smart Grids for Elevated Renewable Implementation -- 3.3 IoT Increasing the Adoption of Renewable Systems -- 3.4 Contribution from End Consumers -- 3.5 Balancing Supply and Demand -- 3.6 Cost-Effectiveness -- 4 Significant Role of Big Data Analytics in the Renewable Energy Sector -- 4.1 Data Forecasting -- 4.2 Efficient Resource Management -- 4.3 Intelligent Storage of Resources -- 4.4 Improving Safety and Reliability -- 4.5 Predicting Transformer Breakdowns and Prevention -- 5 Maharashtra Using Drones in EHV Power Transmission Lines and Towers -- 6 Long-Distance Drones Used for Surveillance to Avoid Network Failures -- 7 Conclusions -- References. |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xii, 109 Seiten Illustrationen, Diagramme |
| ISBN: | 9789811610103 978-981-16-1010-3 |