Renewable Energy Systems

Modeling, Optimization and Applications
Herausgeber: Kumar, Sanjay; Upadhyay, Subho; Kumar, Sandeep; Gupta, Nikita

• Gebundenes Buch

Produktbeschreibung

Providing updated and state-of-the-art coverage of a rapidly changing science, this groundbreaking new volume presents the latest technologies, processes, and equipment in renewable energy systems for practical applications. This groundbreaking new volume examines recent advances in the area of renewable energy systems, including modeling and optimization using different methods like GAMS, HOMER, AI techniques and MATLAB Simulink, and others. Covering extensively diverse topics ranging from solar radiation prediction model to improving solar power output by studying the tilt and orientation angle of rooftop-mounted systems, a multitude of practical applications are covered, offering solutions to everyday problems, as well as the theory and concepts behind the technology. Among these applications are increasing the longevity of PV by studying its degradation and its use by operating an electrolyzer for hydrogen production, using biodiesel as a green energy resource as an alternative to diesel fuel, concentrating the black liquor-based biomass as a source from multiple stage evaporator along with thermo-vapour compressor, and the real-time problems of modeling and optimizing renewable energy sources. Written and edited by a global team of experts, this groundbreaking new volume from Scrivener Publishing presents recent advances in the study of renewable energy systems across a variety of fields and sources. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.

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Produktdetails

• Verlag: Wiley
• Seitenzahl: 544
• Erscheinungstermin: 1. November 2022
• Englisch
• Abmessung: 235mm x 157mm x 34mm
• Gewicht: 931g
• ISBN-13: 9781119803515
• ISBN-10: 1119803519
• Artikelnr.: 62924726

Autorenporträt

Col Sanjay Kumar is an alumnus of Indian Military Academy and was commissioned into the Corps of Engineers. The officer is a B Tech in Civil Engineering and a M Tech in Transportation Engineering from IIT Kharagpur. The officer has served as United Nations Military Observer in Democratic Republic of Congo and in Bhutan as Colonel (Works & Planning) of Border Roads Organization's Project Dantak. The book is a result of the officer's Research Fellowship with USI of India, New Delhi.

Inhaltsangabe

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