Artificial Intelligence for Renewable Energy systems

Ashutosh Kumar Dubey, Sushil Narang, Abhishek Kumar, Vicente García-Díaz, Arun Lal Srivastav

• Publisher: Woodhead Publishing
• Year: 2022
• ISBN:
  9780323906616
• Topic: Ciencias físicas
• Subtopic: Energía

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

Table of contents

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