Photovoltaic Systems Technology

✍ Scribed by Mohammed Aslam Husain, Md Waseem Ahmad, Farhad Ilahi Bakhsh, P. Sanjeevikumar, Hasmat Malik

• Publisher: Scrivener Publishing, Wiley Blackwell
• Year: 2024
• Tongue: English
• Leaves: 279
• Category: Library

✦ Table of Contents

Cover
Series Page
Title Page
Copyright Page
Contents
List of Contributors
Preface
Chapter 1 History of Solar PV System and its Recent Development
1.1 Introduction
1.2 Solar Photovoltaic (PV)
1.3 Historical Overview
1.4 Grid-Connected PV System
1.4.1 PV Module
1.4.2 PV Array and Cells
1.4.3 Solar Inverter
1.4.3.1 Central Inverter
1.4.3.2 Module Inverter
1.4.3.3 String Inverter
1.4.3.4 Multi String Inverter
1.4.4 Characteristics of Solar Inverter
1.4.5 Battery Storage in PV System
1.5 Power Losses in PV System
1.6 Different MPPT and Solar Tracker
1.6.1 Perturb and Observe (P&O) Algorithm
1.6.2 Incremental Conductance Algorithm
1.6.3 Fractional Short-Circuit Current (FSCC) Algorithm
1.6.4 Artificial Intelligence (AI) Algorithms
1.7 Development in Standalone PV System
1.8 The Development and Challenges in DC–DC Converter for PV Applications
1.8.1 Recent Development in Microinverters for PV Applications
1.9 PV-Powered Electric Vehicles
1.10 Discussion
1.11 Conclusion
References
Chapter 2 Evolution and Modeling of Solar Photovoltaic Cells: From Early to Modern Concepts
2.1 Introduction
2.2 History of Solar Cell
2.3 Solar PV Cell Formation
2.4 Solar Cell Models
2.5 Applications
2.6 Conclusion
References
Chapter 3 Clustering of Panels and Shade Diffusion Techniques for Partially Shaded PV Array–Review
3.1 Introduction
3.2 Reconfiguration of PV Array
3.2.1 Modeling of PV Cell
3.2.2 Definition of PV Reconfiguration
3.3 Classification of Reconfiguration Strategies
3.3.1 Static Reconfiguration Strategies
3.3.1.1 Sudoku Algorithm
3.3.1.2 TomTom Pattern
3.3.1.3 Chaotic Baker Method
3.3.1.4 Magic Square Technique
3.3.1.5 Futoshiki Puzzle Algorithm
3.3.1.6 Zig-Zag Approach
3.3.1.7 Odd Even Approach
3.3.1.8 Skyscraper Method
3.3.2 Dynamic Reconfiguration Strategies
3.3.2.1 Electrical Array Reconfiguration Method
3.3.2.2 Genetic Algorithm (GA)
3.3.2.3 Particle Swarm Optimization
3.3.2.4 Artificial Intelligence Algorithm
3.3.2.5 Adaptive Array Reconfiguration
3.3.2.6 Irradiation Equivalence by Relocation of Panels
3.3.2.7 Grasshopper Optimization Algorithm
3.3.2.8 Modified Harris Hawk Optimizer Algorithm
3.4 Conclusion
References
Chapter 4 Advances in Solar PV-Powered Electric Vehicle Charging System
4.1 Introduction
4.2 Overview of Electric Vehicle (EV) Charging System
4.3 Evolution of Electric Vehicles
4.4 Classification of Electric Vehicle (EV) Charging Stations
4.4.1 Residential/Home Charging Station
4.4.2 Public Charging Station
4.4.3 Charging During Park
4.4.4 Fifteen Minutes Less Charging or Charging Swabs
4.5 Approaches to PV-EV Charging System
4.5.1 Solar PV Grid-Charging Station
4.5.2 Solar PV Standalone Charging Station
4.5.2.1 Solar PV Standalone Charging Station Without Battery Storage Unit (BSU)
4.5.2.2 Solar PV Standalone Charging Station with Battery Storage Unit (BSU)
4.6 Recharging and Innovative Methods
4.6.1 V2G (Vehicle to Grid) Technology
4.6.2 Hydrogen-Based Energy Storage
4.7 Energy Storage Systems for EV Charging
4.8 Hybrid Energy Storage Technologies to Reduce the Size of the Battery
4.8.1 Hybrid Energy Storage Technologies
4.8.2 Hybrid Energy Storage Challenges
4.8.3 Challenges in Electric Vehicles
4.9 Battery Management System (BMS)
4.10 Conclusion and Future Aspects
References
Chapter 5 A Review of Maximum Power Point Tracking (MPPT) Techniques for Photovoltaic Array Under Mismatch Conditions
5.1 Introduction
5.2 Evaluation of MPPT Techniques
5.2.1 Perturb and Observe (P&O) Technique
5.2.2 Perturb and Observe Algorithm with Variable Step Magnitude
5.2.3 MPPT Based on Incremental Conductance
5.2.4 Artificial Neural Network (ANN)-Based MPPT
5.2.5 The Fuzzy Logic Control (FLC)-Based MPPT
5.2.6 Hill Climbing Control-Based MPPT
5.2.7 Global Maximum Power Point (GMPP) Technique
5.2.8 Particle Swarm Optimization (PSO)-Based MPPT
5.2.9 Constant Voltage-Based MPPT
5.2.10 Constant Current-Based MPPT
5.2.11 Grey Wolf Optimization (GWO) Algorithm
5.2.12 Ant Colony Optimization (ACO)–Based MPPT
5.2.13 Artificial Bee Colony (ABC) Technique
5.2.14 Firefly Algorithm (FA)-Based MPPT
5.2.15 Curve Tracer MPPT
5.2.16 Cuckoo Search (CS)-Based MPPT
5.2.17 Chaotic Search-Based MPPT
5.2.18 Random Search Method (RSM)-Based MPPT
5.3 Conclusion
References
Chapter 6 Metaheuristic Techniques for Power Extraction from PV-Based Hybrid Renewable Energy Sources (HRESs)
Abbreviation
6.1 Introduction
6.2 Hybrid Renewable Energy Systems
6.2.1 Types of Hybrid Renewable Energy Systems
6.2.1.1 Grid-Connected HRE System
6.2.1.2 Stand-Alone or Off-Grid HRE System
6.3 PV Array Characteristics
6.3.1 The I–V and P–V Curves of a Solar PV Cell Under Partially Shaded Conditions
6.4 Evaluation of Various MPPT Methods Using Standard Conventional Approaches
6.5 Evaluation of Various MPPT Methods Using Advanced Approaches (Metaheuristic Optimization Approaches)
6.5.1 Benefits and Restrictions of MPPT Approaches Based on Metaheuristic Optimization
6.6 Conclusion and Future Scope
References
Chapter 7 Intelligent Modeling and Estimation of Solar Radiation Data Using Artificial Intelligence
7.1 Introduction
7.2 The Solar-AI Span: Background and Literature Review
7.3 Modeling and Prediction of Data on Solar Irradiance Using AI Approaches
7.4 Detailed Comparative Analysis of Different AI Approaches Used in Modeling and Forecasting of Data on Solar Radiation
7.5 Discussion
7.6 Conclusion
References
Chapter 8 Application of ANN–ANFIS Model for Forecasting Solar Power
8.1 Introduction
8.1.1 Motivation and Significance
8.1.2 Literature Survey
8.1.3 Research Gap
8.1.4 Novelty
8.2 Overview of ANN
8.2.1 Models of ANN
8.3 ANFIS Architecture
8.3.1 ANFIS Layers
8.4 Characterization of Solar Plant
8.5 Classification of Weather Condition
8.6 Statistical Performance Indicators
8.6.1 MAPE
8.6.2 n-MAE
8.7 Development of ANN–ANFIS Model
8.8 Results
8.8.1 Type-a (Sunny) Model
8.8.2 Type-b (Hazy) Model
8.8.3 Type-c (Rainy) Model
8.8.4 Type-d (Cloudy) Model
8.8.5 Comparative Analysis of the ANN–ANFIS Models with Fuzzy Logic Model
8.9 Conclusions
Acknowledgments
Conflict of Interest
ORCID
References
Chapter 9 Machine Learning Application for Solar PV Forecasting
9.1 Introduction
9.2 Literature Review
9.3 Research Methods and Materials
9.3.1 Dataset
9.4 Proposed Work
9.4.1 ARIMA Model
9.5 Experimental Simulation, Result Analysis, Comparison, and Discussion
9.5.1 Data Reprocessing
9.5.2 Simulation
9.5.3 Comparison and Discussion
9.6 Conclusion
References
Chapter 10 Techno-Economic Comparative Analysis of On-Ground and Floating PV Systems: A Case Study at Gangrel Dam, India
Description of Symbols/Abbreviations
10.1 Introduction
10.2 Project Site Assessment for Various Parameters
10.3 Design of On-Ground and Floating PV Systems
10.3.1 On-Ground Photovoltaic System
10.3.2 Floating PV System
10.4 Simulation, Results and Analysis
10.4.1 On-Ground PV System
10.4.1.1 Monthly Energy Production
10.4.1.2 Annual Energy Production
10.4.1.3 Loss Diagram
10.4.1.4 Analysis of Greenhouse Gas Emission
10.4.2 Floating PV System
10.4.2.1 Effect of Reservoir Water Level on Power Output of Associated Hydropower Plant
10.4.2.2 Effect on PV System Structure Material, Flora–Fauna of Water and Other Activities
10.4.3 Comparative Analysis Between On-Ground PV System and Floating PV System
10.4.3.1 Comparison Based on Other Parameters
10.5 Conclusion
References
Chapter 11 BLDC Motor Driven Water Pumping System Powered by Solar Photovoltaics (PV)
11.1 Introduction
11.2 Interaction of PV Array and Load
11.3 Application of DC–DC Converter for MPPT
11.4 Three-Phase BLDC Motor
11.5 Simulation of Suggested Technique
11.6 Conclusion
References
Appendix
Chapter 12 Hybrid Photovoltaic/PEM Fuel Cell Driven Water Pumping System for Agricultural Application: Overview, Challenges and Future Perspectives
12.1 Introduction
12.2 Mathematical Modeling
12.2.1 PEMFC System
12.2.2 PV System
12.3 MATLAB/Simulink Study of Hybrid FC/PV Powered Water Pumping System
12.4 Electrical Water Pumping System Categories
12.5 Challenges of Hybrid PV/PEMFC Technology
12.5.1 Challenges of Hydrogen Production and Storage
12.5.2 Challenges of the Hybrid PV/PEMFC System Integration
12.5.3 Hybrid PV/FC Power System Ignorance and Acceptance
12.6 Future Scope of Hybrid PV/PEMFC Water-Pumping Systems
12.7 Pros and Cons of Hybrid PV/PEMFC-Powered Water-Pumping System
12.8 Conclusion
References
Index
Also of Interest
EULA