This book provides a comprehensive overview of the role of modeling in advancing perovskite solar cell technology and its implications for the future of renewable energy. It encompasses various aspects of perovskite solar cell modeling, including computational modeling and simulation techniques, experimental validation methods, optimization strategies, and performance evaluation metrics.
Features
:
• Discusses the basic principles, working mechanisms, materials, and designing approaches related to the implementation of perovskite solar cells.
• Covers electron and hole transport models, computational approaches to charge transport, and transport in different perovskite structures.
• Illustrates the crystal structure, composition, optical and electronic properties, stability, and degradation mechanisms of perovskite materials.
• Explains tandem solar cell design principles, interface engineering for tandems, and stability challenges in tandem solar cells.
• Explores the performance parameters related to perovskite solar cells and the implementation of such devices.
It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electrical and communications engineering, energy engineering, renewable energy, and computer science and engineering.
The text provides a comprehensive overview of the role of modeling in advancing perovskite solar cell technology and its implications for the future of renewable energy. It includes various aspects of perovskite solar cell modelling.
Chapter
1. An Introduction to the Solar Energy: A Step Towards
Sustainability.
Chapter
2. Fundamentals of Perovskite Materials.
Chapter
3.
Technology Advancements in Solar Cells: A Summary.
Chapter
4. Recent Advances
in Perovskite Tandem Solar Cells for Enhanced Solar Efficiency.
Chapter
5.
Modelling Techniques of Perovskite Solar Cells.
Chapter
6. Modeling the
Future of Renewable Energy: Machine Learning in Solar Energy Prediction.
Chapter
7. Optimizing Hybrid Electric Vehicle Performance by Deep Learning
for Power Distribution and Regenerative Braking Prediction in Urban Driving
Conditions.
Chapter
8. Optimization of Power for Solar Panel Optimizer Using
Different FPGAs.
Chapter
9. Advancing Solar Energy with Machine Learning,
Perovskite Technology, and Smart Data Systems.
Chapter
10. Machine Learning
for Performance Prediction and Optimization.
Chapter
11. Machine Learning
Applications in Solar Energy: Predicting Performance and Efficiency.
Chapter
12. A Novel Hybrid LSTM-XGBoost Model for Enhanced Solar PV Power Generation
Forecasting.
Chapter
13. A Comprehensive Review of Cybersecurity Challenges
in Solar Grids.
Chapter
14. Harnessing Machine Learning for Solar Energy
Forecasting: Advancing Perovskite Solar Cells and Renewable Energy Solutions.
Chapter
15. Toward Secure Solar Energy Systems: A Cyber Perspective.
Chapter
16. Thermal and Power Efficient Hardware Design of Solar Panel on
Reconfigurable Architecture.
Chapter
17. Solar Charge Controller Design on
FPGA.
Chapter
18. Exploring the Role of Solar Energy in Advancing
Agricultural Practices.
Chapter
19. Machine Learning in Solar Energy
Prediction.
Chapter
20. Real-Time Solar Panel Performance Monitoring and
Energy Forecasting.
Chapter
21. Solar Energy to Sustainable Development
Goals: A Case Study.
Chapter
22. Advancements and Challenges in
All-Perovskite Tandem Solar Cells: A Critical Review
Arthur James Swart is currently working as an Associate Professor in the Department of Electrical Electronics and Computer Engineering at the Central University of Technology, South Africa. His research interests include engineering education and alternative energy. He worked for Telkom SA and De Beers Namaqualand Mines for 4 years. He joined the Vaal University of Technology in 1995 and progressed from a Technician to a Senior Lecturer in 2007. He completed his MEd in 2007 and his DTech in 2011. He has always loved teaching, but his passion for research took time to develop. Research affords one the opportunity to engage in lifelong learning, which will always remain his primary goal and which he is currently pursuing at the Central University of Technology.
Keshav Kumar is an Assistant Professor in the Department of Electronics and Communication Engineering at Pranveer Singh Institute of Technology, Kanpur, India. He is pursuing his PhD in the field of Hardware Security from Lingayas Vidyapeeth, Faridabad, India. He has previously worked at Chandigarh University, Punjab, India (NIRF 29). He completed his Master of Engineering in ECE with a specialization in Hardware Security from Chitkara University, Punjab, India. He has also worked as a Junior Research Fellow (JRF) at NIT Patna and as an Assistant Lecturer at Chitkara University, Punjab, India. He has authored and couthored many books and more than 55 research papers in the fields of hardware security, green communication, lowower VLSI design, machine learning techniques, and IoT. He has also worked with professors from 20 different countries. His areas of specialization include deep learning, hardware security, green communication, lowower VLSI design, machine learning techniques, wireless sensor network (WSN), and IoT. He has experience in teaching Python programming, embedded systems, IoT, computer networks, and digital electronics. He is also associated with Gyancity Research Consultancy Pvt Ltd. He is also a member of IAENG. He has more than 600 citations (Google Scholar), 15 Hindex (Google Scholar), and 12 HIndex (Scopus).
Bishwajeet Pandey is a Professor at GL Bajaj College of Technology and Management, Greater Noida, India. He has been a Senior Member of IEEE since 2019. He holds an MTech in Computer Science and Engineering from the Indian Institute of Information Technology, Gwalior, India, and a PhD in Computer Science from the Gran Sasso Science Institute, Italy. He has taught at esteemed institutions such as Chitkara University Chandigarh; Birla Institute of Applied Science, Bhimtal; Jain University, Bangalore; Astana IT University, Kazakhstan; Eurasian National University, Kazakhstan (QS World Rank 321); and UCSI University, Malaysia (QS World Rank 265). He is a prolific researcher, with 11 published books, 196 research papers indexed in Scopus, 45 papers in SCIE, and a total of 296 papers. He has garnered over 3,600 citations and holds an Hindex of 28. His leadership roles include serving as the Research Head of the School of Computer Science and Engineering at Jain University, Bangalore (20212023), and as the Head of the International Global Academic Partnership Committee at Birla Institute of Applied Science, Bhimtal (20202021). In 2023, he was honored with the prestigious Professor of the Year Award at Lords Cricket Ground by the London Organisation of Skills Development. Beyond his outstanding research output, his greatest strength lies in his global academic network. He has visited 49 countries, participated in 105 international conferences, and couthored papers with 218 professors from 93 universities across 42 nations.
Sakshi Sharma is currently working as a Junior Research Fellow at the School of Advanced Engineering, University of Petroleum and Energy Studies, Dehradun, India. She is pursuing her PhD in Photovoltaic Systems from the University of Petroleum and Energy Studies, Dehradun, India. She successfully completed her Master of Engineering in ECE with the specialization in Hardware Security from Chitkara University, Punjab, India. She has also worked as an Assistant Lecturer at Chitkara University, Punjab, India.
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