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Elsevier

Artificial Intelligence for Renewable Energy systems

  • 1 Edición - 1 de agosto de 2022
  • Última edición
  • Editores: Ashutosh Kumar Dubey, Sushil Narang, Abhishek Kumar, Vicente García-Díaz, Arun Lal Srivastav
  • Idioma: Inglés

Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy sy… Leer más

Descripción

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.

Puntos claves

  • 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

De interès para

Both renewable energy researchers and practicing engineers, working in the fields of AI and Renewable Energy. Mostly research with up-and-coming practical applications included

Índice

1. Current State of energy systems

2. Artificial Intelligence and Machine Learning implications to energy systems

3. Weather forecasting using Artificial Intelligence

4. Intelligent Energy storage

5. Modelling and Simulation of Power Electronic Circuits

6. Control methods in Renewable energy systems

7. Role of Artificial Intelligence in Power Quality Management and Stability Analysis

8. Integration of microgrids

9. Rooftop photovoltaic systems

10. Biomass and biogas

11. Renewable energy systems and technologies education

12. Evolutionary Intelligence in Renewable energy

13. Smart Energetic Management

14. RnE: Renewable Energetic Systems

15. Energy efficient lighting systems

16. Scope of Artificial Intelligence based solar energy system

17. Role of Artificial Intelligence in environmental sustainability

18. Integration of Artificial Intelligence with biomethanation

19. Hybrid renewable energy system and Artificial Intelligence

20. Renewable energy and sustainable developments

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 11 de agosto de 2022
  • Idioma: Inglés

Sobre los editores

AD

Ashutosh Kumar Dubey

Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. He is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Ciudad Real, Spain.
Afiliaciones y experiencia
Department of Computer Science and Engineering, Institute of Engineering and Technology, Chitkara University, India

SN

Sushil Narang

Dr. Sushil Kumar Narang is Dean and an Associate Professor in the Department of Computer Science & Engineering at Chitkara University, Rajpura, Punjab since 2019. From 2006-2019, He was head of IT department at SAS Institute of IT & Research, Mohali, Punjab. From 1996-2006 he was Assistant Professor at Department of Computer Science & Applications, MLN College, Yamuna agar, Haryana. He Completed his Ph.D. at Panjab University, Chandigarh. His Research on “Feature Extraction and Neural Network Classifiers for Optical Character Recognition for Good quality handwritten Gurmukhi and Devnagari Characters” focused on various image processing, machine as well as deep learning algorithms. His research interests lie in the area of programming languages, ranging from theory to design to implementation, Image Processing, Data Analytics and Machine Learning. He has collaborated actively with researchers in several other disciplines of computer science, particularly Machine Learning on real world use cases.
Afiliaciones y experiencia
Dean and Associate Professor, Department of Computer Science and Engineering at Chitkara University, Rajpura, Punjab, India

AK

Abhishek Kumar

Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He holds a Ph.D. in Computer Science from the University of Madras and is currently a Post-Doctoral Fellow with the Ingenium Research Group, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He received his M.Tech in Computer Science and Engineering and B.Tech in Information Technology from Rajasthan Technical University, Kota, India. He has over thirteen years of academic teaching experience. His research interests include Artificial Intelligence, Computer Vision, Image Processing, Data Mining, Machine Learning, and Renewable Energy Systems.

Afiliaciones y experiencia
Chandigarh University, Punjab, India

VG

Vicente García-Díaz

Dr. Vicente García-Díaz is a Software Engineer and has a PhD in Computer Science. He is an Associate Professor in the Department of Computer Science at the University of Oviedo. He is also part of the editorial and advisory board of several journals and has been editor of several special issues in books and journals. He has supervised 80+ academic projects and published 80+ research papers in journals, conferences and books. His research interests include decision support systems, Domain-Specific languages and eLearning.
Afiliaciones y experiencia
Associate Professor, Department of Computer Science, University of Oviedo, Spain

AS

Arun Lal Srivastav

Arun Lal Srivastav is working as Professor and Associate Dean (Research), Tulas University, Dehradun, Uttarakhand, India. He has done post-doctoral research at National Chung Hsing University, Taiwan. His research interests include water quality surveillance, climate change, water treatment, river ecosystem, soil health maintenance, engineering education, phytoremediation and waste management. He worked on 04 Government sponsored projects (worth ~16 million INR) on phytoremediation, adsorption, capacity building, organic farming, leachate treatment, agro-waste management etc. He received the prestigious "Teachers Associateship for Research Excellence (TARE) Fellowship" followed by a research grant from the Science and Engineering Research Board (SERB), Govt. of India in 2022.

Afiliaciones y experiencia
Professor and Associate Dean (Research), Department of Applied Sciences and Engineering, Tulas University, Dehradun, Uttarakhand, India

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