Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies Krishna Kumar
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Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies – Ebook Instant Download/Delivery ISBN(s): 9780323912280,0323912281
Product details:
- ISBN-10 : 0323912281
- ISBN-13 : 978-0323912280
- Author(s):
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development.
As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation.
Table contents:
Chapter 1: Application of alternative clean energy
Chapter 2: Optimization of hybrid energy generation
Chapter 3: IoET-SG: Integrating internet of energy things with smart grid
Chapter 4: Evolution of high efficiency passivated emitter and rear contact (PERC) solar cells
Chapter 5: Online-based approach for frequency control of microgrid using biologically inspired intelligent controller
Chapter 6: Optimal allocation of renewable energy sources in electrical distribution systems based on technical and economic indices
Chapter 7: Optimization of renewable energy sources using emerging computational techniques
Chapter 8: Advanced renewable dispatch with machine learning-based hybrid demand-side controller: The state of the art and a novel approach
Chapter 9: A machine learning-based design approach on PCMs-PV systems with multilevel scenario uncertainty
Chapter 10: Agent-based peer-to-peer energy trading between prosumers and consumers with cost-benefit business models
Chapter 11: Machine learning-based hybrid demand-side controller for renewable energy management
Chapter 12: Prediction of energy generation target of hydropower plants using artificial neural networks
Chapter 13: Response surface methodology-based optimization of parameters for biodiesel production
Chapter 14: Reservoir simulation model for the design of irrigation projects
Chapter 15: Effect of hydrofoils on the starting torque characteristics of the Darrieus hydrokinetic turbine
References
Index
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