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Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization de Amit Kumar Yadav

Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization

Autor Amit Kumar Yadav, Hasmat Malik, Majed A. Alotaibi
en Limba Engleză Paperback – 18 iul 2025
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.


  • Presents novel intelligent techniques with step-by-step coverage for improved optimum tilt angle calculation for the installation of photovoltaic systems
  • Provides coding and modeling for data-driven techniques in prediction and forecasting
  • Covers intelligent data-driven techniques for solar energy forecasting and prediction
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Specificații

ISBN-13: 9780443134821
ISBN-10: 0443134820
Pagini: 302
Dimensiuni: 152 x 229 mm
Greutate: 0.38 kg
Editura: ELSEVIER SCIENCE

Public țintă

Academic: Researchers, scientists, and advanced students across solar energy, renewable energy, electrical engineering, AI and machine learning, computer science and information technology, control engineering, mechanical engineering, and electronics. Industry: Engineers, 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 more generally.

Cuprins

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

Notă biografică

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.