Perovskite Solar Cells

Modeling the Future of Renewable Energy

Arthur James Swart, Keshav Kumar, Bishwajeet Pandey, Sakshi Sharma

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040426197
• Topic: Tecnología e ingeniería
• Subtopic: Ingeniería eléctrica y telecomunicaciones

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.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Preface
• About the editors
• List of contributors
• 1 An introduction to the solar energy: A step toward sustainability
• 2 Fundamentals of perovskite materials
• 3 Technology advancements in solar cells: A summary
• 4 Recent advances in perovskite tandem solar cells for enhanced solar efficiency
• 5 Modelling techniques of perovskite solar cells
• 6 Modeling the future of renewable energy: Machine learning in solar energy prediction
• 7 Optimising hybrid electric vehicle performance by deep learning for power distribution and regenerative braking prediction in urban driving conditions
• 8 Optimization of power for solar panel optimizer using different FPGAs
• 9 Advancing solar energy with machine learning, perovskite technology, and smart data systems
• 10 Machine learning for performance prediction and optimization
• 11 Machine learning applications in solar energy: Predicting performance and efficiency
• 12 A novel hybrid LSTM-XGBoost model for enhanced solar PV power generation forecasting
• 13 A comprehensive review of cybersecurity challenges in solar grids
• 14 Harnessing machine learning for solar energy forecasting: Advancing perovskite solar cells and renewable energy solutions
• 15 Toward secure solar energy systems: A cyber perspective
• 16 Thermal and power-efficient hardware design of solar panel on reconfigurable architecture
• 17 Solar charge controller design on FPGA
• 18 Exploring the role of solar energy in advancing agricultural practices
• 19 Machine learning in solar energy prediction
• 20 Real-time solar panel performance monitoring and energy forecasting
• 21 Solar energy to sustainable development goals: A case study
• 22 Advancements and challenges in all-perovskite tandem solar cells: A critical review
• Index