Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included.
This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems.
1. Applications of AI and IOT in Renewable Energy - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. v 6. List of contributors - p. xi 7. Chapter one Machine learning algorithms used for short-term PV solar irradiation and temperature forecasting at microgrid - p. 1 8. Chapter two Generators’ revenue augmentation in highly penetrated renewable M2M coordinated power systems - p. 19 9. Chapter three Intelligent supervisory energy-based speed control for grid-connected tidal renewable energy system for efficiency maximization - p. 33 10. Chapter four An intelligent energy management system of hybrid solar/wind/battery power sources integrated in smart DC microgrid for smart university - p. 57 11. Chapter five IoT in renewable energy generation for conservation of energy using artificial intelligence - p. 89 12. Chapter six Renewable energy system for industrial internet of things model using fusion-AI - p. 107 13. Chapter seven Centralized intelligent fault localization approach for renewable energy-based islanded microgrid systems - p. 129 14. Chapter eight Modeling of electric vehicle charging station using solar photovoltaic system with fuzzy logic controller - p. 151 15. Chapter nine Weather-based solar power generation prediction and anomaly detection - p. 169 16. Chapter ten RMSE and MAPE analysis for short-term solar irradiance, solar energy, and load forecasting using a Recurrent Artificial Neural Network - p. 181 17. Chapter eleven Study and comparative analysis of perturb and observe (P&O) and fuzzy logic based PV-MPPT algorithms - p. 193 18. Chapter twelve Control strategy for design and performance evaluation of hybrid renewable energy system using neural network controller - p. 211 19. Index - p. 225
Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included.
This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems.
1. Applications of AI and IOT in Renewable Energy - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. v 6. List of contributors - p. xi 7. Chapter one Machine learning algorithms used for short-term PV solar irradiation and temperature forecasting at microgrid - p. 1 8. Chapter two Generators’ revenue augmentation in highly penetrated renewable M2M coordinated power systems - p. 19 9. Chapter three Intelligent supervisory energy-based speed control for grid-connected tidal renewable energy system for efficiency maximization - p. 33 10. Chapter four An intelligent energy management system of hybrid solar/wind/battery power sources integrated in smart DC microgrid for smart university - p. 57 11. Chapter five IoT in renewable energy generation for conservation of energy using artificial intelligence - p. 89 12. Chapter six Renewable energy system for industrial internet of things model using fusion-AI - p. 107 13. Chapter seven Centralized intelligent fault localization approach for renewable energy-based islanded microgrid systems - p. 129 14. Chapter eight Modeling of electric vehicle charging station using solar photovoltaic system with fuzzy logic controller - p. 151 15. Chapter nine Weather-based solar power generation prediction and anomaly detection - p. 169 16. Chapter ten RMSE and MAPE analysis for short-term solar irradiance, solar energy, and load forecasting using a Recurrent Artificial Neural Network - p. 181 17. Chapter eleven Study and comparative analysis of perturb and observe (P&O) and fuzzy logic based PV-MPPT algorithms - p. 193 18. Chapter twelve Control strategy for design and performance evaluation of hybrid renewable energy system using neural network controller - p. 211 19. Index - p. 225
