Machine Learning and the Internet of Things in Solar Power Generation

✍ Scribed by Prabha Umapathy, Abinaya Inbamani, Suman Lata Tripathi, Jude Hemanth, Shelej Khera

• Publisher: CRC Press
• Year: 2023
• Tongue: English
• Leaves: 190
• Series: Smart Engineering Systems: Design and Applications
• Category: Library

✦ Synopsis

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

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface to the first edition
Chapter organization
Editors bios
List of Contributors
Chapter 1: Solar analytics using AWS serverless services
1.1 Introduction
1.1.1 Solar thermal power
1.2 Related work
1.3 Internet of Things (IoT)
1.4 The use of contemporary technologies in system design
1.5 Serverless solar data analytics
1.6 Conclusion
References
Chapter 2: Study of conventional & non-conventional SEPIC converter in solar photovoltaic system using Proteus
2.1 Introduction
2.2 SEPIC converter in the open-loop system
2.3 SEPIC converter in the closed-loop system
2.4 Conclusion
References
Chapter 3: Design and implementation of non-inverting buck converter based on performance analysis scheme
3.1 Introduction
3.2 Non-reversing buck-boost converter
3.2.1 Operating modes of NIBB converter-buck mode
3.2.2 Operating modes of NIBB converter – boost mode
3.2.3 Design equations of NIBB converter [ 15 ]
3.3 Simulation results of NIBB converter
3.4 Computation of output voltage ripple for NIBB converters based on different duty cycle
3.4.1 Values
3.5 Conclusion
References
Chapter 4: Investigation of various solar MPPT techniques in solar panel
4.1 Introduction
4.1.1 PV module
4.2 Problem statement
4.3 Methodology
4.3.1 MPPT algorithms for uniform irradiance
4.3.1.1 Perturb and observe
4.3.1.2 Hill climbing
4.3.1.3 Incremental conductance
4.3.1.4 Load current maximization
4.3.2 MPPT algorithms for partial shading condition
4.3.2.1 Particle Swarm Optimization (PSO)
4.3.2.2 Artificial Neural Network (ANN)
4.4 Simulation and performance comparison
4.4.1 Modeling and simulation of 60W PV array ( Figures 4.14–4.19)
4.4.2 Comparison of MPPT techniques for varying conditions of solar irradiation
4.5 Conclusion
References
Chapter 5: Real-time solar farm performance monitoring using IoT
5.1 Introduction
5.2 Proposed system design
5.3 Hardware design
5.3.1 Electrical characteristics
5.3.2 Thermal characteristics
5.3.3 PV array design
5.3.4 LoRa technology
5.3.5 Communication pattern of LPWAN
5.3.6 Gateway information management technique
5.3.7 Functional requirements
5.3.7.1 Measurement of monitoring parameters
5.3.7.2 Collection of monitoring parameters
5.3.7.3 Modeling measurement system
5.3.7.4 Visualization of measured parameters
5.3.7.5 Wireless monitoring and reporting
5.3.8 Fault detection model
5.3.9 Data analysis GUI application
5.3.10 Software design
5.4 Results and discussion
5.5 Conclusion
5.5.1 Recommendation
5.5.1.1 Measurement
5.5.1.2 Data collection
5.5.1.3 Modeling
5.5.1.4 Data visualization
5.5.1.5 Remote detection and reporting
5.5.1.6 Future work
References
Chapter 6: Solar energy forecasting architecture using deep learning models
6.1 Introduction
6.2 Deep learning approach
6.3 A sample multilayer architecture
6.4 Data mining process for renewable energy
6.5 Solar forecasting architecture
6.5.1 Data collection
6.5.2 Dataset
6.5.3 Data preprocessing and feature selection
6.5.4 Model training and parameterization
6.6 Solar power forecasting prediction techniques
6.6.1 RNN
6.6.2 GRU
6.6.3 LSTM
6.7 Performance results
6.8 Results and discussion
References
Chapter 7: Characterization of CuO–SnO 2 composite nano powder by hydrothermal method for solar cell
7.1 Introduction
7.2 Sample preparation method
7.2.1 Preparation of CuO–SnO 2 thin film
7.2.2 Characterization techniques
7.3 Results and discussion
7.3.1 Structural properties
7.3.2 Scanning Electron Microscope (SEM)
7.3.3 Transmission electron microscopy analysis
7.4 Optical properties
7.5 Diode and solar applications
7.6 Characteristics
7.7 Conclusion
References
Chapter 8: Design and development of solar PV based advanced power converter topologies for EV fast charging
8.1 Introduction to electric vehicle charging
8.2 DC–DC converters
8.2.1 Boost converter
8.2.2 Buck-boost converter
8.3 DC–DC converter for DC fast charging
8.3.1 Snubber assist zero-voltage zero-current (SAZZ) converter for EV applications
8.3.1.1 Modes of operation
8.3.2 Re-lift converter
8.3.3 Bi-directional DC–DC converter
8.3.4 Boost mode or step-up mode of bidirectional DC–DC converter
8.4 Conclusion
References
Chapter 9: Assessment of different MPPT techniques for PV system
9.1 Introduction
9.2 Modeling of PV panel
9.3 MPPT procedures
9.3.1 Incremental conductance technique
9.3.2 Perturb and observe procedure
9.3.3 Altered P&O process
9.4 Results and discussions
9.5 Conclusion
References
Index