1 Importance of Hybrid Energy System in Reducing Greenhouse Emissions 1Rupan 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 29Tarlochan 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 61Mukesh 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 91Himanshu 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 117Saurabh 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 139Pallavi 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 167Sumit 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 191Rajesh 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 217Smitarani 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 247Ravinder 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 265Shubham 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 295Sudipta 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 327Vineet 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 365Nitish 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 379Subho 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 403Anand 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 453Kamaldeep, 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 469Neha 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

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.