Applications of AI and IOT in Renewable Energy (eBook, ePUB)

Redaktion: Shaw, Rabindra Nath; Balas, Valentina Emilia; Mekhilef, Saad; Ghosh, Ankush

• Format: ePub

Produktbeschreibung

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 The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles.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.

• Includes future applications of AI and IOT in renewable energy
• Based on case studies to give each chapter real-life context
• Provides advances in renewable energy using AI and IOT with technical detail and data

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 246
• Erscheinungstermin: 9. Februar 2022
• Englisch
• ISBN-13: 9780323984010
• Artikelnr.: 63418979

Autorenporträt

Rabindra Nath Shaw is a Senior Member of IEEE (USA), currently holding the post of Director, International Relations, Galgotias University India. He is an alumnus of the applied physics department, University of Calcutta, India. . He has more than eleven years teaching experience in leading institutes like Motilal Nehru National Institute of Technology Allahabad, India, Jadavpur University and others in UG and PG level. He has successfully organised more than fifteen International conferences as Conference Chair, Publication Chair and Editor. He has published more than fifty Scopus/ WoS/ ISI indexed research papers in International Journals and conference Proceedings. He is the editor of several Springer and Elsevier books. His primary area of research is optimization algorithms and machine learning techniques for power system, IoT Application, Renewable Energy, and power Electronics converters. He also worked as University Examination Coordinator, University MOOC's Coordinator, U

niversity Conference Coordinator and Faculty- In Charge, Centre of Excellence for Power Engineering and Clean Energy Integration.

Inhaltsangabe

1. Machine Learning Algorithms Used for Short-Term PV Solar irradiation and Temperature Forecasting at Microgrid 2. Generators' Revenue Augmentation in Highly Penetrated Renewable M2M coordinated Power Systems 3. Intelligent Supervisory Energy-Based Speed Control for Grid-Connected Tidal Renewable Energy System Efficiency Maximization 4. An Intelligent Energy Management System of Hybrid Solar/Wind/Battery Power Sources Integrated in Smart DC Microgrid for Smart University 5. IoT in Renewable Energy Generation for Conservation of Energy Using Artificial Intelligence 6. Renewable Energy System for Industrial Internet of Things Model Using Fusion-AI 7. Centralized Intelligent Fault Localization Approach for Renewable Energy-based Islanded Microgrid Systems 8. Modelling of EV charging station using Solar Photovoltaic (PV) system with Fuzzy Logic Controller 9. Weather-based Solar Power Generation Prediction and Anomaly Detection 10. RMSE and MAPE analysis for short term Solar Irradiance, Solar Energy and Load Forecasting using Recurrent Artificial Neural Network 11. Study and Comparative Analysis of Perturb and Observe (P&O) and Fuzzy Logic Based PV-MPPT Algorithms 12. Control strategy for design and performance evaluation of hybrid system using neural network controller