Machine Learning and the Internet of Things in Solar Power Generation
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Machine Learning and the Internet of Things in Solar Power Generation

Machine Learning and the Internet of Things in Solar Power Generation

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About the Book

The book investigates various MPPT algorithms, and the optimization of solar energy using machine learning and deep learning. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental. This book: Discusses data acquisition by the internet of things for real-time monitoring of solar cells. Covers artificial neural network techniques, solar collector optimization, and artificial neural network applications in solar heaters, and solar stills. Details solar analytics, smart centralized control centers, integration of microgrids, and data mining on solar data. Highlights the concept of asset performance improvement, effective forecasting for energy production, and Low-power wide-area network applications. Elaborates solar cell design principles, the equivalent circuits of single and two diode models, measuring idealist factors, and importance of series and shunt resistances. The text elaborates solar cell design principles, the equivalent circuit of single diode model, the equivalent circuit of two diode model, measuring idealist factor, and importance of series and shunt resistances. It further discusses perturb and observe technique, modified P&O method, incremental conductance method, sliding control method, genetic algorithms, and neuro-fuzzy methodologies. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental.

Table of Contents:
Chapter 1 Study of Conventional & Non-Conventional SEPIC Converter in Solar Photovoltaic System using Proteus. Shreyas Rajendra Hole and Dr.Agam Das Goswami Chapter 2 Solar analytics using AWS serverless services. Parul Dubey and Dr. Arvind Tiwari Chapter 3 Design and Implementation of Non Inverting Buck Converter based on Performance Analysis scheme Dr.M.Siva Ramkumar, R.Felshiya Rajakumari Chapter 4 Investigation of various solar MPPT techniques in solar panel Ms. Divya R, Dr. Pavithra C V and Dr. Sundaram M Chapter 5 Real-Time Solar Farm Performance Monitoring using IoT Mr. E. Kannapiran, Dr. S. Jaganathan, Mr. N.R. Govinthasamy and Ms. E. Kalaivani Chapter 6 SOLAR ENERGY FORECASTING ARCHITECTURE USING DEEP LEARNING MODELS Mrs.R.R.Rubia Gandhi ,Dr.C.Kathirvel,Mr.R.Mohan Kumar and Dr.M.Siva Ramkumar Chapter 7 CHARACTERIZATION OF CuO-SnO 2 COMPOSITE NANO POWDER by hydrothermal method for solar cell Dr.K.Srinivasan,Dr.V.Rukkumani,Dr.V.Radhika,Dr.M.Saravanakumar and Ms.S.Kavitha Chapter 8 Automation in Agricultural Robot for Farming and Seeding Purpose Using Solar PV R.Felshiya Rajakumari and Dr.M.Siva Ramkumar Chapter 9 Design and development of solar PV based advanced power converter topologies for EV fast charging S.S.Karthikeyan and Dr. R.UTHIRASAMY Chapter 10 ASSESSMENT OF DIFFERENT MPPT TECHNIQUES FOR PV SYSTEM Mr. M. Karthik and Mrs. N. Divya


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Product Details
  • ISBN-13: 9781000894295
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Language: English
  • ISBN-10: 1000894290
  • Publisher Date: 14 Jul 2023
  • Binding: Digital (delivered electronically)


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Machine Learning and the Internet of Things in Solar Power Generation
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Machine Learning and the Internet of Things in Solar Power Generation
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