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The book summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It provides incites to the solar cell, biofuels, wind and other renewable energy system design and characterization, including the equipment for smart energy systems.
List of contents
Chapter 1: Artificial Intelligence: A New Era in Renewable Energy Systems. Chapter 2: Role of AI in Renewable Energy Management. Chapter 3: AI-based Renewable Energy with Emerging Applications: Issues and Challenges. Chapter 4: Foundations of Machine Learning. Chapter 5: Introduction of AI techniques and Approaches. Chapter 6: A Comprehensive Overview of Hybrid Renewable Energy Systems. Chapter 7: Dynamic Modelling and Performance Analysis of Switched-Mode Controller for Hybrid Energy Systems. Chapter 8: Artificial Intelligence and Machine Learning Methods for Renewable Energy. Chapter 9: Artificial Neural Network Based Power Optimizer for Solar Photovoltaic System: An Integrated Approach with Genetic Algorithm. Chapter 10: Predictive Maintenance: AI Behind Equipment Failure Prediction. Chapter 11: AI Techniques for the Challenges in Smart Energy Systems. Chapter 12: Energy Efficiency. Chapter 13: Renewable Energy from Plant Biomass and Photosynthetic Organisms and its Operations. Chapter 14: Evolving Trends for Smart Grid Using Artificial Intelligent Techniques. Chapter 15: Introduction to AI techniques for Photovoltaic Energy Conversion System. Chapter 16: Deep Learning Based Fault Identification of Micro Grid Transformers. Chapter 17: Power Quality Improvement for Grid Integrated Renewable Energy Sources: A Comparative analysis of UPQC Topologies. Chapter 18: AI based Energy Efficient Fault Mitigation Technique for Reliability Enhancement of Wireless Sensor Network. Chapter 19: AI Techniques Applied to Wind Energy. Chapter 20: Comparative Performance Analysis of Multi-Objective Metaheuristic Approaches for Parameter Identification of Three-Diode Modelled Photovoltaic Cells. Chapter 21: Artificial Intelligence Techniques in Smart Grid. Chapter 22: Parameter Identification of a New Reverse Two Diode Model by Moth Flame Optimizer. Chapter 23: Time-Series Energy Prediction and Improved Decision Making.
About the author
Suman Lata Tripathi is working as a Professor at School of Electronics and Electrical Engineering, Lovely Professional University, India.
Mithilesh Kumar Dubey is working as an Associate Professor at School of Computer Science and Engineering, Lovely Professional University, India.
Vinay Rishiwal is working as a Professor at Department of Computer Science and Information Technology, Faculty of Engineering and Technology, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India.
Sanjeevikumar Padmanaban is working as a faculty member, at Department of Energy Technology, Aalborg University, Esbjerg, Denmark.
