Amit Kumar Yadav, Hasmat Malik, Majed A Alotaibi

Intelligent Data Analytics for Solar Energy Prediction and Forecasting

Advances in Resource Assessment and Pv Systems Optimization

• Broschiertes Buch

Produktbeschreibung

Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource.

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Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 350
• Erscheinungstermin: 1. Mai 2025
• Englisch
• Gewicht: 450g
• ISBN-13: 9780443134821
• ISBN-10: 0443134820
• Artikelnr.: 67734953

Autorenporträt

Dr. Amit Kumar Yadav received his B.Tech in Electrical and Electronics Engineering in 2009 from United College of Engineering and Research Naini Allahabad Uttar Pradesh, India, M.Tech. in Power Systems in 2011, and Ph.D. in artificial neural network-based prediction of solar radiation for optimum sizing of photovoltaic systems for power generation in 2016, from the Centre for Energy and Environmental Engineering National Institute of Technology, Hamirpur, Himachal Pradesh, India. Currently, he is faculty in the Electrical and Electronics Engineering Department, National Institute of Technology, Sikkim, India. Dr. Yadav has authored numerous articles in international journals, 10 book chapters, and 12 IEEE conference publications, is an Editorial Board Member of the Turkish Journal of Forecasting, and acts as a reviewer for a number of journals. He received an award as "Best Researcher In Solar Photovoltaic Systems For Maximum Power Generation? in the Research Under Literal Access (RULA) International Awards in 2019. His research interests include Solar Photovoltaics, Engineering Optimization, Artificial Neural Network, Soft Computing, Wind Speed and Solar Radiation Prediction/Forecasting, Solar and Wind Resource Assessment, and Condition Monitoring of Photovoltaic Systems.

Inhaltsangabe

PART A: Solar Energy Prediction and Forecasting Resources 1. Intelligent
Data Analytics Tools and Techniques 2. Solar Energy Prediction and
Forecasting Resource Assessment PART B: Market Research and Survey of
Intelligent Data Analytics for Solar Energy Prediction and Forecasting 3.
Intelligent Data Analytics in Solar Irradiance Prediction 4. Intelligent
Data Analytics for Tilt Angle Optimization of PV Systems 5. Intelligent
Data Analytics for Electrical Characteristics of Solar PV Modules PART C:
Intelligent Data Analytics Methods for Solar Energy Prediction and
Forecasting 6. Intelligent Data Analytics for Feature Extraction and
Selection in Solar Radiation Prediction and Forecasting 7. Intelligent Data
Analytics for Tilt Angle Optimization for Installation of Solar PV Systems
for Maximum Power Generation 8. Intelligent Data Analytics to Analyze the
Effect of Tilt Angle on Optimum Sizing and Power Generation of Standalone
PV Systems 9. ntelligent Data Analytics to Analyze the Optimum Tilt Angle
Influences on Grid Connected PV Systems 10. Intelligent Data Analytics for
Maximum Power Prediction of Photovoltaic Modules in Outdoor Conditions 11.
Intelligent Data Analytics for Daily Array Yield Prediction of
Grid-Interactive Solar PV (GISPV) Plants