Advances of Artificial Intelligence in a Green Energy Environment

1st Edition - May 20, 2022
Editors: Pandian Vasant, Joshua Thomas, Elias Munapo, Gerhard-Wilhelm Weber
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 8 9 7 8 5 - 3
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 8 8 5 7 4 - 4

Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage… Read more

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Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern.

Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy.

Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.

Cover image
Title page
Table of Contents
Copyright
Contributors
About the editors
Preface
Acknowledgments
Chapter 1. Application of some ways to intensify the process of anaerobic bioconversion of organic matter
1.1. Introduction
1.2. Methods for improving the process of methane digestion of manure and manure runoff and their analysis
1.3. Application results
1.4. Energy model
1.5. Conclusion
Chapter 2. Disasters impact assessment based on socioeconomic approach
2.1. Introduction
2.2. Statistics and tendencies of natural and man-made disasters
2.3. Overview of institutions dealing with risk management
2.4. Promising approaches to decrease risks and losses caused by disasters
2.5. The issues of effective disaster countering organization
2.6. Socioeconomic approach to the estimations of risk dynamics
2.7. Conclusions
Appendix A: An example of selecting the optimal list of prevention or mitigation measures
Chapter 3. Uninterruptible power supply system of the consumer, reducing peak network loads
3.1 Introduction
3.2 Methodology of the work
3.3 Work results
3.4. Conclusions
Chapter 4. Optimization of the anaerobic conversion of green biomass into volatile fatty acids for further production of high-calorie liquid fuel
4.1. Introduction
4.2. Experimental part and methods
4.3. Results and discussion
4.4. Conclusions
Chapter 5. Life cycle cost and life cycle assessment: an approximation to understand the real impacts of the Electricity Supply Industry
5.1. Importance of Electricity Supply Industry
5.2. The economics of Electricity Supply Industry
5.3. The life cycle of Electricity Supply Industry
5.4. Importance of life cycle assessment of Electricity Supply Industry
5.5. Life cycle cost of Electricity Supply Industry
5.6. Mobilizing industry for a clean and circular economy
Chapter 6. Comparison of open access multi-objective optimization software tools for standalone hybrid renewable energy systems
6.1. Introduction
6.2. Literature review
6.3. Open access multi-objective optimization tools
6.4. Case study
6.5. Conclusion
Chapter 7. Optimization of the organic waste anaerobic digestion in biogas plants through the use of a vortex layer apparatus
7.1. Introduction
7.2. Anaerobic processing of organic waste: general characteristics of fermentation
7.3. Methods of preprocessing
7.4. Vortex layer apparatus
7.5. Application of the vortex layer apparatus in biogas plants
7.6. Conclusion
Chapter 8. Search of regularities in data: optimality, validity, and interpretability
8.1. Introduction
8.2. Occam's razor principle for verification of parametric regression models
8.3. Occam's razor principle for verification of regression models based on optimal partitioning
8.4. Conclusion
Chapter 9. Artificial intelligence techniques for modeling of wind energy harvesting systems: a comparative analysis
9.1. Introduction
9.2. Review of related works
9.3. Modeling of wind energy harvesting system
9.4. Maximum power point tracking system
9.5. Load side converter control
9.6. Results and discussion
9.7. Conclusion
Chapter 10. Human paradigm and reliability for aggregate production planning under uncertainty
10.1. Introduction
10.2. Literature review
10.3. Discussion and conclusion
Chapter 11. Artificial intelligence–based intelligent geospatial analysis in disaster management
11.1. Introduction
11.2. Related work
11.3. Proposed work
11.4. Performance analysis
11.5. Conclusion
Chapter 12. Optimizing the daily use of limited solar panels in closely located rural schools in Zimbabwe
12.1. Introduction
12.2. Modeling the solar panel problem
12.3. TSP network features
12.4. Dummies and their use in elimination of subtours
12.5. Proposed algorithm for TSP
12.6. Other applications of the traveling salesman
12.7. Conclusions
Chapter 13. Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics
13.1. Introduction
13.2. Economic load/emission dispatch
13.3. Bioenergy and biofuel supply chains
13.4. Sustainable capacity planning and optimization
13.5. Outlook
Chapter 14. Hybrid optimization and artificial intelligence applied to energy systems: a review
14.1. Introduction
14.2. Stochastic programming
14.3. Optimization in energy systems
14.4. Conclusions
Chapter 15. A brief literature review of quantitative models for sustainable supply chain management
15.1. Introduction
15.2. Theoretical foundation and literature reviews
15.3. Methodology
15.4. Results
15.5. Discussion
15.6. Conclusion
Chapter 16. Optimized designing spherical void structures in 3D domains
16.1. Introduction
16.2. Problem formulation
16.3. Mathematical model
16.4. Mathematical model with balancing conditions
16.5. Numerical experiments
16.6. Conclusions
Chapter 17. Swarm-based intelligent strategies for charging plug-in hybrid electric vehicles
17.1. Introductions
17.2. Problem formulation
17.3. Swarm-based intelligence approaches
17.4. Results and discussions
17.5. Conclusions
Index

Pandian Vasant

Pandian Vasant is a Research Associate at MERLIN Research Centre, TDTU in Vietnam. He holds a PhD in Computational Intelligence, an MSc in Engineering Mathematics, and a BSc in Mathematics. His research interests include soft computing, hybrid optimization, holistic optimization, innovative computing, and applications.

Affiliations and expertise

Research Associate at MERLIN Research Centre, TDTU in Vietnam

Joshua Thomas

J. Joshua Thomas is an Associate Professor at UOW Malaysia KDU Penang University College. He obtained his PhD (Intelligent Systems Techniques) from University Sains Malaysia, Penang, and master’s degree from Madurai Kamaraj University, India. He is working with deep learning algorithms, specially targeting on graph convolutional neural networks and bidirectional recurrent neural networks for drug target interaction and image tagging with embedded natural language processing. His work involves experimental research with software prototypes and mathematical modeling and design.

Affiliations and expertise

Associate Professor, UOW Malaysia KDU Penang University College, Malaysia

Elias Munapo

Elias Munapo holds a BSc in Applied Mathematics, an MSc in Operations Research, and a PhD in Applied Mathematics, all from the National University of Science and Technology (N.U.S.T.) in Zimbabwe. Elias has vast experience in university education and has worked for five institutions of higher learning. He was a lecturer at Zimbabwe Open University, Chinhoyi University of Technology, and University of South Africa. He became a Senior Lecturer at the University of KwaZulu-Natal and then joined North West University as an Associate Professor in 2016 and has been appointed as a Professor since January 2019.rofessor

Affiliations and expertise

Professor, North West University, South Africa

Gerhard-Wilhelm Weber

Gerhard-Wilhelm Weber is a Professor at Poznan University of Technology, Poznan, Poland, at Faculty of Engineering Management, in the Chair of Marketing and Economic Engineering. His research is on data mining, analytics, AI, machine learning, mathematics, operational research, finance, economics, optimization and optimal control, neuro-, bio-, and earth sciences, medicine, and development; he is involved in the organization of scientific life internationally.

Affiliations and expertise

Professor, Poznan University of Technology, Poland

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Advances of Artificial Intelligence in a Green Energy Environment

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Pandian Vasant

Joshua Thomas

Elias Munapo

Gerhard-Wilhelm Weber