Renewable Energy Systems

Renewable Energy Systems

Modeling, Optimization and Applications

Upadhyay, Subho; Kumar, Sanjay; Kumar, Sandeep; Gupta, Nikita

John Wiley & Sons Inc

10/2022

544

Dura

Inglês

9781119803515

15 a 20 dias

666

Descrição não disponível.
1 Importance of Hybrid Energy System in Reducing Greenhouse Emissions 1
Rupan Das, Somudeep Bhattacharjee and Uttara Das

1.1 Introduction 2

1.2 Scenario of Climate Change in the World 5

1.3 Role of a Hybrid Framework Based on Renewable Energy 7

1.4 Proposed Model Description 10

1.5 Mathematical Model of Hybrid System 11

1.5.1 Solar PV System 11

1.5.2 Wind Energy System 12

1.5.3 Diesel Generator 13

1.5.4 Renewable Voltage Stabilizing Controller 14

1.5.5 Inverter 14

1.6 Simulation Model of the Hybrid Energy System 15

1.6.1 Solar PV System Simulation 16

1.6.2 Wind Energy System Simulation 17

1.6.3 Diesel Generator Simulation 17

1.6.4 Renewable Voltage Stabilizing Controller Simulation 17

1.7 Results of Simulation Analysis 19

1.7.1 Hybrid Renewable Energy System Simulation Results 19

1.7.2 Solar PV Simulation Results 19

1.7.3 Wind Generation System Simulation Results 20

1.7.4 Inverter Simulation Result 21

1.8 Conclusion and Discussion 22

Acknowledgments 23

References 23

2 Experimental Study on Tilt Angle and Orientation of Rooftop PV Modules for Maximising Power Output for Chandigarh, India 29
Tarlochan Kaur, Isha Arora, Jaimala Gambhir, Ravneet Kaur and Ayush Gera

2.1 Introduction 30

2.2 Literature Review 32

2.3 Experimental Setup 37

2.3.1 Location Under Study 37

2.3.2 Experimental Setup 38

2.3.3 Methodology Used 40

2.4 Experimental Results and Discussion 40

2.4.1 Orientation Optimisation of PV Modules 40

2.4.2 Tilt Angle Optimisation of PV Modules 43

2.4.2.1 Absolute Maximum Monthly Energy Values Method 43

2.4.2.2 Weighted Frequency Count (WFC) Method 43

2.4.2.3 Weighted Maximum Energy (WME) Method 44

2.4.3 Mutual Shading of PV Modules on Account of Row Spacing 45

2.5 Latitude and Optimal Tilt Angle 52

2.6 Conclusions and Future Scope 54

Acknowledgment 55

References 56

3 Biodiesel, Challenges and Solutions 61
Mukesh Kumar and Mahendra Pal Sharma

3.1 Introduction 62

3.2 Significant Challenges Faced by Biodiesel 62

3.2.1 Low Oil Yields and Slow Growth Rate 62

3.2.2 Selection of Potential Feedstocks 63

3.3 Conversion of Microalgae into Biodiesel 66

3.3.1 Transesterification 66

3.3.2 Direct (In Situ) Transesterification 74

3.4 Microalgae Biodiesel 76

3.5 Conclusion 81

References 82

4 Comparative Overview of a Novel Configuration of a DC-AC Converter with Reduced Components 91
Himanshu Sharma, Kamaldeep and Rahul Dogra

4.1 Introduction 91

4.2 The Novel Topology 94

4.2.1 State of Operation of the Proposed Inverter 95

4.2.1.1 First Operating Mode 95

4.2.1.2 Second Operating Mode 96

4.2.1.3 Third Operating Mode 97

4.2.2 Boost Factor Calculation 97

4.2.3 RMS Value of the Output Voltage 98

4.3 Performance Characteristics 98

4.3.1 Boost Factor and Shoot-Through Duty Ratio Variation 98

4.3.2 Output Voltage Variation with Shoot-Through Duty Ratio 99

4.3.3 Boost Factor and THD Variation 100

4.3.4 Capacitor Voltage Stress 104

4.4 Modulation Technique 104

4.5 Simulation Results 106

4.5.1 Simulation Results with MATLAB 106

4.5.2 Simulation Results with Real-Time Simulator 109

4.6 Critical Analysis of Proposed Topology with the Conventional Z-Source Inverter 111

4.7 Conclusion 113

References 114

5 Intelligent Sliding Mode Controller for Wind Energy Powered DC Nanogrid 117
Saurabh Kumar, Vijayakumar K., Ashok Bhupathi Kumar Mukkapati and Rajvir Kaur

5.1 Introduction 118

5.2 Overview of Wind Energy Conversion System 122

5.3 System Description 124

5.4 Controller Description 125

5.4.1 Particle Swarm Optimization 130

5.5 Results and Analysis 131

5.5.1 Comparative Study 133

5.6 Conclusion 135

References 136

6 Grid Integration of Renewable Energy Systems 139
Pallavi Verma, Rachana Garg and Priya Mahajan

6.1 Introduction 139

6.2 Modelling of Grid-Interconnected Solar PV System 141

6.2.1 SPV System 142

6.2.2 DC-DC Converter 143

6.2.3 PV Inverter 144

6.3 Design of Grid-Interconnected Solar PV System 144

6.3.1 Design of Solar PV Array 144

6.3.2 Inductor for Boost Converter (Lb) 144

6.3.3 Selection of Diode and IGBT for Boost Converter 145

6.3.4 Choice of DC-Link Voltage (Vdc) 145

6.3.5 Sizing of DC-Link Capacitor (Cdc) 146

6.3.6 Interfacing Inductors (Lr) 146

6.4 PV Inverter Control Techniques 147

6.4.1 Synchronous Reference Frame Theory 147

6.4.2 Unit Template-Based Control Algorithm 149

6.4.3 Fuzzy Logic Control (FLC) Algorithm 150

6.4.3.1 Fuzzification 150

6.4.3.2 Inference Process 150

6.4.3.3 Defuzzification 151

6.4.4 LMS-Based Adaptive Control Algorithm 151

6.5 MATLAB/Simulink Results and Discussion 154

6.5.1 Linear/Non-Linear Load Under Steady-State Condition 154

6.5.2 Linear/Non-Linear Load Under Dynamic Condition 156

6.5.3 Linear/Non-Linear Load with Change in Irradiation 158

6.5.4 Linear/Non-Linear Unbalanced Loading Condition 160

6.5.5 Comparison of LMS-Based Adaptive Control Algorithm with Other Control Algorithms in Terms of Total Harmonics Distortion (THD) 161

6.6 Conclusion 162

Appendix 162

References 163

7 Modeling and Analysis of Autonomous Hybrid Green Microgrid System for the Electrification of Rural Area 167
Sumit Sharma, Yog Raj Sood, Ankur Maheshwari and Pallav

7.1 Introduction 167

7.2 Renewable Energy Technologies 174

7.3 Economic Evaluation 175

7.4 Microgrid Protection 177

7.5 Simulation Results and Discussion 179

7.5.1 MIC - A: SPV/Wind/Biomass Generator/ Hydro/Battery/Converter 182

7.5.2 MIC - B: SPV/Wind/Diesel Generator/ Hydro/Battery/Converter 182

7.6 Conclusion 185

References 186

8 Performance Optimization of a Pine Oil-Fueled Agricultural Engine Using Grey - Taguchi Approach 191
Rajesh Kumar, Manoj Gwalwanshi, Vikas Verma, Rahul Tarodiya and Manoj Kumar

8.1 Introduction 192

8.1.1 Taguchi Method 196

8.1.2 Grey Relational Analysis 197

8.2 Experimental Setup and Procedure 198

8.2.1 Experimental Setup 198

8.2.2 Error Analysis 200

8.3 Grey-Taguchi Analysis 200

8.4 Taguchi - SN Ratio 207

8.4.1 Analysis of Variance (ANOVA) 208

8.4.2 Confirmatory Experiments 209

8.5 Results and Discussion 210

8.6 Conclusion 211

Acknowledgment 211

References 211

9 Nonlinear Mathematical Modeling and Energy Optimization of Multiple-Stage Evaporator Amalgamated with Thermo-Vapor Compressor 217
Smitarani Pati, Om Prakash Verma, Varun Sharma and Tarun Kumar Sharma

9.1 Introduction 219

9.2 Process Description 223

9.3 Nonlinear Energy Modeling 224

9.3.1 Material Balance Equations 226

9.3.2 Energy Balance Equations 226

9.3.3 Thermo-Vapor Compressor (TVC) 228

9.4 Formulation of the Objective Function 229

9.5 Solution Approach 230

9.6 Result and Discussion 232

9.7 Validity of the Proposed Model 234

9.8 Conclusion 242

References 243

10 Fuel Cell Fed Shunt Active Power Filter for Power Quality Issue by Electric Vehicle Charging 247
Ravinder Kumar and Hari Om Bansal

10.1 Introduction 247

10.2 Specification of the Fuel Cell Integrated SAPF 249

10.2.1 Proton Exchange Membrane Fuel Cell 250

10.3 Reference Current Generation 252

10.3.1 ANFIS-Based Control Algorithm 254

10.4 Discussion and Simulation Findings 255

10.5 Results and Discussion in Real Time 258

10.6 Conclusions 261

References 261

11 In-Depth Analysis of Various Aspects of Charging Station Infrastructure for Electric Vehicle 265
Shubham Mishra, Shrey Verma, Gaurav Dwivedi and Subho Upadhyay

11.1 Introduction 265

11.2 Classification of Electric Vehicles 268

11.2.1 Hybrid Electric Vehicles (HEVs) 269

11.2.2 Plug-In Electric Vehicles (PEVs) 269

11.2.3 Fuel Cell Electric Vehicles (FCEVs) 269

11.3 Energy Storage Technologies Used in EVs 269

11.3.1 Battery 270

11.3.2 Super Capacitor (SC) 271

11.3.3 Flywheel 271

11.3.4 Hydrogen Storage 271

11.4 Types of Electric Vehicle Charging Station (EVCS) 271

11.5 Aspects and Challenges in the Development of EV Charging Infrastructure 271

11.5.1 Determining the Optimal Location for Establishing Ev Charging Stations 273

11.5.2 Ensuring an Optimized and Well-Planned Operation Management 273

11.5.3 Reducing EV Charging Time by Establishment of High-Class Charging Techniques and Battery Swapping Method 274

11.5.4 Strategically Handling the Queues of EVs at the Charging Station 275

11.5.5 Establishing a Promising Structure for Integration with Grid 275

11.5.6 A Proper Communication Channel for Managing the Grid Operation 275

11.5.7 Impact on the Environment by EV Charging Station Infrastructure 276

11.5.8 Impact on Power System Expansion by an Increased Rate of EV Adoption 276

11.5.9 Proper Sizing of Energy Storage Technologies 276

11.5.10 Sizing and Proper Methodology for the Use of Renewable Energy Technologies that will Fulfill the Electricity Demand of the Charging Station with or Without Integrating with the Power Grid 277

11.5.11 Use of Energy Storage Technologies and Charging Techniques to Enhance Stability 278

11.5.12 Determining the Peak Hours for Managing the Charging Load Demand on the Grid for Stable Operation 279

11.5.13 Estimating a Customer-Friendly as well as Profit-Making Charging Rate 280

11.6 Developments in the Sector of Electric Vehicles and its Charging Stations in India 281

11.7 Conclusion 283

References 284

12 Optimization of PV Electrolyzer for Hydrogen Production 295
Sudipta Saikia, Vikas Verma, Sivasakthivel Thangavel, Rahul Tarodiya and Rajesh Kumar

12.1 Introduction 296

12.2 Hydrogen as a Potential Fuel for the Future 297

12.3 Properties of Hydrogen 298

12.4 Fundamental Concepts of Hydrogen Production Processes 299

12.4.1 Water Electrolysis - Thermodynamic Reactions 300

12.4.2 Factors Impacting the Rate of Efficiency of Water Electrolysis 302

12.4.3 Classification of Electrolyzers 303

12.4.4 Selection Criterion of Electrodes 305

12.4.5 Effects of Changing Operating Parameters, Sizes and Electrolytic Concentration 306

12.5 System Description and Components 307

12.6 Electrochemical Equations 308

12.7 Methodology 310

12.7.1 Taguchi Technique 310

12.7.2 Taguchi - Design of Experiments 311

12.7.3 Steps of Taguchi Technique 312

12.8 Results and Discussion 314

12.8.1 Taguchi Process - Operating Factors for the Perforated Electrolyzer 314

12.8.2 Taguchi Process - Result of Signal-to-Noise (S/N) Ratio 317

12.8.3 Taguchi Process - Analysis of Variance (anova) 319

12.8.4 Confirmation Test 319

Conclusions 322

References 323

13 Assessment of GAMS in Power Network Applications Including Wind Renewable Energy Source 327
Vineet Kumar, R. Naresh, Veena Sharma and Vineet Kumar

13.1 Introduction 328

13.1.1 General Background and Motivation 329

13.1.2 Goal and Challenging Focus 330

13.2 Importance and a User's View on GAMS Software 333

13.2.1 Models for Academic Research 334

13.2.2 Models for Domain Expert 335

13.2.3 Black Box Models 336

13.3 The Basic Structure in the GAMS Environment 337

13.3.1 Input Command 339

13.3.2 Output Command 340

13.4 Power System Applications Using GAMS Software 340

13.4.1 Multi-Area Economic Dispatch (ED) 341

13.4.2 AC Optimal Power Flow 344

13.5 Development Trends in GAMS 355

13.6 Conclusion 357

Acknowledgments 358

References 358

14 Multi-Objective Design of Fractional Order Robust Controllers for Load Frequency Control 365
Nitish Katal and Sanjay Kumar Singh

14.1 Introduction 366

14.2 Mathematical Model of Single Area Load Frequency Control 367

14.3 Background 368

14.3.1 Fractional-Order PID Controllers 368

14.3.2 Multiverse Optimizer 369

14.4 Proposed Method to Tune PID Controller 370

14.4.1 Formulation of Optimization Problem 370

14.4.1.1 Formulation of Objective Function Related to Time-Domain Response 370

14.4.1.2 Formulation of Objective Function Related to Robust Control 371

14.5 Results and Discussions 371

14.5.1 Optimal Controller Synthesis Using Time Domain Approaches 372

14.5.2 Optimal Robust Controller Synthesis 372

14.6 Frequency Deviation for 0.02 p.u. Load Change 375

14.7 Conclusions 376

Nomenclature 376

References 377

15 Challenges and Remedies of Grid-Integrated Renewable Energy Resources 379
Subho Upadhyay and Ashwini Kumar Nayak

15.1 Introduction 380

15.2 Developing a Cost-Effective and Adequate Stand-Alone or Grid-Connected Generation System in a Hilly Area 381

15.3 Challenges of Grid-Connected Hybrid Energy System 383

15.4 Energy Management 385

15.4.1 Cycle Charging Strategy 386

15.4.2 Load Following Strategy 386

15.4.3 Peak Shaving Strategy 387

15.5 Frequency Deviation 387

15.6 Voltage Deviation 389

15.7 Adequacy Assessment of Intermittent Sources 389

15.7.1 Failure Rate of PV System 390

15.7.1.1 Configuration of PV Plant 390

15.7.1.2 Calculation of Forced Outage Rate of Solar PV System 393

15.7.2 Failure Rate of Wind System 393

15.7.2.1 WTG Output as a Function of Wind Speed 393

15.7.2.2 Determination of DAFOR Using Apportioning Method 394

15.7.2.3 Reducing Multistate WECS Using the Apportioning Method 395

15.7.3 Power System Planning 396

15.8 Conclusion 398

References 399

16 Solar Radiations Prediction Model Using Most Influential Climatic Parameters for Selected Indian Cities 403
Anand Mohan and Gopal Singh

16.1 Introduction 403

16.2 Introduction to Solar Energy 404

16.3 Energy Status 405

16.3.1 World Energy Status 405

16.3.2 India Energy Status 405

16.3.3 Himachal Pradesh Energy Status 406

16.4 Existing Solar Technologies 407

16.4.1 Solar Thermoelectric Technology 407

16.4.2 Photovoltaic Technology 407

16.4.2.1 High Efficiency 408

16.4.2.2 Thin Films 408

16.4.2.3 Organic and Dye-Sensitised 408

16.5 Existing Solar Modeling Techniques 408

16.5.1 Angstrom Model 408

16.5.2 Angstrom-Prescott Model 409

16.5.3 Lieu and Jordan Model 410

16.6 Relevance for Solar Electrification in Himachal Pradesh 414

16.7 Literature Review 414

16.7.1 Related Researches 414

16.7.2 Gaps in Research Drawn from Literature 418

16.7.3 Estimation of Solar Radiation Potential 418

16.7.4 Objectives of the Research 419

16.8 Methodology Used 420

16.8.1 Prediction Model Developed Using Artificial Neural Networks 420

16.8.2 Potential Assessment Using ANN 420

16.8.3 Identification of Most Influential Parameters 420

16.8.4 Artificial Neural Network - A Better Prediction Tool 420

16.8.5 Artificial Neural Networks vs. Regression 424

16.9 Prediction Model Using Adaptive Neuro-Fuzzy Inference System (ANFIS) 424

16.9.1 Potential Assessment Using ANFIS 425

16.10 Different Input Variables 426

16.10.1 Most Relevant Input Data Selection 426

16.10.2 Development of a Database for Different Models 426

16.10.3 Designing of Different Models 427

16.10.4 Calculation of Maximum Absolute Percentage Error 428

16.10.5 Selection of Most Suitable Models 428

16.11 Prediction Model for Ten Selected Cities of Himachal Pradesh 428

16.11.1 Selection of Input Variables Used for Prediction Model Using ANN 428

16.11.2 ANN Dependent Solar Radiation Estimation Models 431

16.12 Sensitivity Test and Error Evaluation of SRPM Models 431

16.13 Results and Discussion of ANN Model 432

16.14 Selection of Inputs Used for Prediction Model Using ANFIS 442

16.15 ANFIS-Based Solar Radiation Prediction Models 442

16.16 Results and Discussion of ANFIS Model 447

References 447

17 Quality Improvement by Eliminating Harmonic Using Nature-Based Optimization Technique 453
Kamaldeep, Himanshu Sharma, Sanjay Kumar, Arjun Tyagi and Rahul Dogra

17.1 Introduction 454

17.2 Cascaded H-Bridge Multilevel Inverter 455

17.3 Harmonic Elimination 456

17.4 Particle Swarm Optimization (PSO) 458

17.5 Simulation Results 462

17.6 Conclusion 466

References 467

18 Effect of Degradations and Their Possible Outcomes in PV Cells 469
Neha Kumari, Sanjay Kumar Singh and Sanjay Kumar

18.1 Introduction 470

18.1.1 Photovoltaic Cells - An Approach to a Greener World 470

18.2 Basics of Photovoltaic Cell 472

18.2.1 History of Semiconductors 473

18.2.2 Basics of Semiconductors 473

18.2.3 Photovoltaic Effect 474

18.2.4 Photovoltaic Cell Efficiency 475

18.3 Photovoltaic Technology 476

18.3.1 First-Generation Technology - Photovoltaic Cells Based on Crystalline Silicon Wafer 476

18.3.1.1 Monocrystalline Silicon Solar Cells (mc-Si) 477

18.3.1.2 Polycrystalline Silicon Solar Cells (pc-Si) 477

18.3.1.3 Heterojunction Solar Cells (HIT) 477

18.3.1.4 PERC Solar Cells 477

18.3.2 Second-Generation Technology - Photovoltaic Cells Based on Thin Films 477

18.3.2.1 Amorphous Silicon Solar Cells (a-Si) 478

18.3.2.2 Cadmium Telluride Solar Cells (CdTe) 478

18.3.2.3 Copper Indium Gallium Selenium Solar Cells (CIGS) 479

18.3.3 Third-Generation Technology - Photovoltaic Cells Based on Innovative Technology 479

18.3.3.1 Organic Solar Cells 480

18.3.4 Emerging Technologies 481

18.4 Degradation in Photovoltaics 481

18.4.1 What is Degradation? 481

18.4.2 Types of Degradation in Photovoltaic Cells and Its Consequences 491

18.4.2.1 Hotspots 491

18.4.2.2 Mechanical Stressing and Cracks 493

18.4.3 Other Types of Degradations 494

18.4.3.1 Corrosion 494

18.4.3.2 Delamination in Photovoltaic Module 495

18.4.3.3 Discoloration in Photovoltaic Module 496

18.4.3.4 Potential Induced Degradation (PID) 496

18.4.3.5 Light-Induced Degradation (LID) 497

18.4.3.6 Interconnection Degradation 497

18.4.3.7 Packaging Material Degradation 498

18.4.3.8 Snail Trails 498

18.5 Current Status and Challenges in Photovoltaic Technologies 499

18.5.1 Crystalline Silicon Photovoltaic Cells 499

18.5.1.1 Current Status and Degradation Level 500

18.5.1.2 Challenges 500

18.5.2 Thin-Film Photovoltaic Cells 500

18.5.2.1 Current Status and Degradation Level 501

18.5.2.2 Challenges 502

18.5.3 The Innovative Technology 503

18.5.3.1 Current Status and Degradation Level 503

18.5.3.2 Challenges 504

18.6 Cost and Efficiency Trends in Photovoltaics Over the Past Decade 504

18.7 Impedance Spectroscopy (IS) - Technique to Identify Degradations in Photovoltaics 505

18.7.1 AC Equivalent Model of Solar Cell 506

18.7.2 Impedance Spectroscopy 507

18.7.3 Procedure for Impedance Spectroscopy 507

18.8 Conclusion 510

References 511

Index 517
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Distributed generation; energy storage system; battery; artificial intelligence; distributed energy resources; electric vehicle, converters; inverters; photovoltaic; fuel cell; wind energy; tidal energy; micro turbines; multilevel inverter; Multiport converter; MPPT; greenhouse gas; Plug-In Hybrid Electric Vehicles; Vehicle-to-Grid (V2G); Vehicle-to-Home (V2H); DC-DC converters; microgrid; Proportional integral controller; current source converter; voltage source converter; Smart grid; power factor correction pulse width modulation; Open loop control; close loop control; nanogrid; Global Warming; IGBT; PWM; Optimization; Efficiency; Reliability; Adaptive control; intelligent control; economic; sizing; power quality