
Advances in AI for Simulation and Optimization of Energy Systems
- 248 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Advances in AI for Simulation and Optimization of Energy Systems
About this book
Advances in AI for Simulation and Optimization of Energy Systems explores AI's groundbreaking role in the future of energy. As the demand for cleaner, more efficient energy systems grows, AI?driven methodologies are leading the way in simulating and optimizing critical processes across the power generation, transmission, and storage sectors. Whether applied to traditional power grids, renewable energy systems, or energy markets, AI techniques such as neural networks, reinforcement learning, fuzzy logic, and metaheuristic optimization are revolutionizing how energy systems are modeled and managed.
This comprehensive volume offers:
- In?depth chapters on AI?driven simulation and optimization strategies
- Case studies that demonstrate real?world applications of AI in energy systems
- An examination of the ethical concerns and legal frameworks surrounding AI
- Cutting?edge methodologies for improving energy technologies' accuracy, efficiency, and performance
Bringing together leading researchers and practitioners in AI and energy systems, this book is an invaluable resource for academics, engineers, and professionals who want to stay ahead of the curve in this rapidly evolving field.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface
- About the Editors
- List of Contributors
- Chapter 1 Fundamentals of Machine Learning Models
- Chapter 2 Applications of Artificial Intelligence Techniques in Power Systems
- Chapter 3 Applications of Artificial Intelligence Techniques in Hybrid Renewable Energy Systems
- Chapter 4 Applications of Artificial Intelligence Techniques in Smart Grid Systems
- Chapter 5 Algae-Based Carbon Sequestration: Optimizing Renewable Energy and Climate Strategy
- Chapter 6 The Use of BWO for Calibration of LFC of a Multi-Area Power System with Real-Life Wind Energy Penetration
- Chapter 7 Advanced Biofuel Generations: Optimizing Sustainable Agriculture and Renewable Energy Transition
- Chapter 8 Hierarchical Robust Optimisation of Chemical Processes and Energy Systems through In-Depth Industrial Data Analysis and Machine Learning
- Chapter 9 Ethical and Legal Aspects of Machine Learning in 5G-Enabled Smart City and Energy Grid Cyber-Defense
- Index