Artificial Intelligence for Solar Photovoltaic Systems
CRC Press (Verlag)
978-1-032-05441-4 (ISBN)
This book provides a clear explanation of how to apply artificial intelligence (AI) to solve the challenges in solar photovoltaic technology. It introduces readers to new AI-based approaches and technologies that help manage and operate solar photovoltaic systems effectively. It also motivates readers to find new AI-based solutions for these challenges by providing a comprehensive collection of findings on AI techniques.
It covers important topics including solar irradiance variability, solar power forecasting, solar irradiance forecasting, maximum power point tracking, hybrid algorithms, swarm optimization, evolutionary optimization, sensor-based sun- tracking systems, single-axis and dual-axis sun-tracking systems, smart metering, frequency regulation using AI, emerging multilevel inverter topologies, and voltage and reactive power control using AI.
This book is useful for senior undergraduate students, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and renewable energy.
Bhavnesh Kumar is an Assistant Professor in the area of power electronics & drives at the Division of Instrumentation & Control Engineering, NSIT Delhi. Bhanu Pratap is working as an Assistant Professor in the Department of Electrical Engineering, National Institute of Technology Kurukshetra, India. Vivek Shrivastava presently is the Dean (Research & Consultancy) at the National Institute of Technology Delhi.
1. History and Application of Solar PV System. 2. Solar Power Forecasting. 3. Comprehensive Technique for Modelling of PV Module. 4. Conventional Techniques for Maximum Power Point Tracking. 5. Intelligent Techniques for Maximum Power Point Tracking. 6. Analysis of Multijunction Solar Cell-Based PV System with MPPT Schemes. 7. Emerging Techniques of Shade Dispersion. 8. Solar Tracking Technology to Harness the Green Energy. 9. Development of Solar Panels Models in Different Countries/Regions. 10. Performance Degradation in Solar Modules. 11. Performance and Reliability Investigation of Practical Microgrid Grid with Photovoltaic Units.
| Erscheinungsdatum | 11.07.2022 |
|---|---|
| Reihe/Serie | Explainable AI XAI for Engineering Applications |
| Zusatzinfo | 38 Tables, black and white; 125 Line drawings, black and white; 16 Halftones, black and white; 141 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 548 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-032-05441-7 / 1032054417 |
| ISBN-13 | 978-1-032-05441-4 / 9781032054414 |
| Zustand | Neuware |
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