Next-Generation Artificial Intelligence Driven Smart and Renewable Energy
- English
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Next-Generation Artificial Intelligence Driven Smart and Renewable Energy
About this book
To provide for a sustainable future, the potential synergies at the dynamic intersection of renewable energy (RE) incorporated with smart energy and artificial intelligence (AI) must be exploited. RE is crucial to preserve the environment. Energy involving various systems must be optimized and assessed to provide better performance. However, the design and development of RE systems remains a challenge. Advanced optimization techniques, AI, and machine learning (ML) plays a crucial role in implementing the latest innovative research in the field of renewable energy-integrated electrical systems. This book also describes the practical challenges encountered, and the solutions and future scope to be adopted. Applications of a variety of advanced optimization and AI techniques in the design and development of RE-integrated systems are discussed to provide new solutions in the RE domain.
Key features:
- Discusses modern modeling/control approaches for improving renewable energy integrating artificial intelligence-driven power systems
- Describes the principles and methods of renewable energy generation technologies, and an analysis of their implementation, management, and optimization, and related economic advantages
- Presents critical information on the technological design and policy issues that must be taken into considered while implementing a smart grid
- Explains of the metaheuristic optimization algorithm for complex electrical systems, and the whale optimization algorithm-based multi-objective hydrothermal scheduling
- Covers the electric vehicle charging station in the distribution network, and transient stability constraint optimal power flow problem using chaotic quasi-oppositional chemical reaction optimization
The topics covered including microgrids, wind power, solar photo voltaic (PV), optimal power flow (OPF), grid connected inverter, electric vehicle, combined heat and power economic dispatch, FACTS tools for smart energy, harmonic impedance of a salient pole synchronous generator (HI), maximum power point tracking (MPPT) and advanced optimization techniques. Next Generation Artificial Intelligence-Driven Smart and Renewable Energy is ideal for academicians, practitioners, teachers, engineers, industry professionals, researchers, and students in diverse fields, including electrical engineering, electronics and communications engineering, energy, and environmental engineering.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Acknowledgments
- List of reviewers
- About the editors
- List of contributors
- 1 Renewable energy: Opportunities, applications, and future scope of artificial intelligence and internet of things
- 2 Machine learning-enhanced maximum power point tracking for solar modules in photovoltaic systems
- 3 An alternative approach to the modeling of harmonic impedance of a salient pole synchronous generator
- 4 Neuro-fuzzy–based optimization techniques
- 5 OPF incorporating FACTS tools with renewable energy by GWA
- 6 Solving of combined heat and power economic dispatch problem using evolutionary technique considering prohibited operating zone
- 7 Integrated modeling and fabrication of electric vehicles for multi-criteria framework-based racing frontier ecosystems
- 8 Application of artificial intelligence in wind energy generation
- 9 Governing and empowering independent power producers in South Africa
- 10 DQ current control strategies for single-phase grid-connected inverter
- 11 Chaotic quasi-oppositional differential search algorithm for transient stability constraint optimal power flow problem
- 12 Illuminating the path to a sustainable future by harnessing AI-powered renewable energy systems
- Index