Artificial Intelligence for Renewable Energy systems
eBook - ePub

Artificial Intelligence for Renewable Energy systems

  1. 406 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence for Renewable Energy systems

About this book

Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms. - Includes real-time applications that illustrates artificial intelligence and machine learning for various renewable systems - Features a templated approach that can be used to explore results, with scientific implications followed by detailed case studies - Covers computational capabilities and varieties for renewable system design

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Yes, you can access Artificial Intelligence for Renewable Energy systems by Ashutosh Kumar Dubey,Sushil Narang,Abhishek Kumar,Vicente García-Díaz,Arun Lal Srivastav in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Sustainability in Architecture. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Artificial Intelligence for Renewable Energy systems
  2. Cover
  3. Title Page
  4. Copyright
  5. Table of Contents
  6. List of Contributors
  7. Preface
  8. 1 Techno-economic study of off-grid renewable energy systems in Pindar and Saryu Valleys, Uttarakhand, India
  9. 2 Analyzing predictive ability of artificial neural network–based short-term forecasting algorithms for temperature and wind speed
  10. 3 Role of renewable energy in attaining sustainable development
  11. 4 Biogas from waste and nanoparticles as renewable energy
  12. 5 Microbial fuel cells
  13. 6 Applying artificial intelligence to predict green concrete compressive strength
  14. 7 Case study analysis of solar tree for public spaces
  15. 8 Recent advances in the production of renewable biofuels using microalgae
  16. 9 Artificial intelligence and technology in weather forecasting and renewable energy systems
  17. 10 Different normalization techniques as data preprocessing for one step ahead forecasting of solar global horizontal irradiance
  18. 11 Artificial intelligence-driven power demand estimation and short-, medium-, and long-term forecasting
  19. 12 Challenges and remediation for global warming to achieve sustainable development
  20. 13 Utilizing artificial intelligence for environmental sustainability
  21. 14 Alleviating biogas generation with waste biomass
  22. 15 Renewable energy and sustainable development
  23. 16 Data-driven predictive model development for efficiency and emission characteristics of a diesel engine fueled with biodiesel/diesel blends
  24. 17 FWS-DL: forecasting wind speed based on deep learning algorithms
  25. Index