LEADER 10245nam 22004693 450 001 9910876878903321 005 20240518060227.0 010 $a1-394-16767-9 010 $a1-394-16766-0 035 $a(CKB)32027832600041 035 $a(MiAaPQ)EBC31342568 035 $a(Au-PeEL)EBL31342568 035 $a(EXLCZ)9932027832600041 100 $a20240518d2024 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPhotovoltaic Systems Technology 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2024. 210 4$dİ2024. 215 $a1 online resource (279 pages) 311 $a1-394-16642-7 327 $aCover -- 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. 327 $a3.3.1.7 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. 327 $a5.2.1 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. 327 $a7.3 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. 327 $a10.4.1.1 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. 700 $aHusain$b Mohammed Aslam$01761005 701 $aAhmad$b Waseem$01761006 701 $aBakhsh$b Farhad Ilahi$01736271 701 $aSanjeevikumar$b P$01753124 701 $aMalik$b Hasmat$01761007 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910876878903321 996 $aPhotovoltaic Systems Technology$94200172 997 $aUNINA