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Renewable Energy Systems

Modeling, Optimization, and Applications
Edited by Sanjay Sharma, Nikita Gupta, Sandeep Kumar, and Subho Upadhyay
Copyright: 2023   |   Status: Published
ISBN: 9781119803515  |  Hardcover  |  
520 pages
Price: $225 USD
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One Line Description
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.

Audience
Electrical, mechanical, petroleum, chemical, and industrial engineers, and scientists, students, and other professionals working in the area of energy and power generation

Description
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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Author / Editor Details
Sanjay Sharma, PhD, is an assistant professor at the University Institute of Technology, Himachal Pradesh University, Shimla, India. He earned his PhD from the Department of Electrical Engineering from Punjab Engineering College Deemed to be University Chandigarh, India in December 2019.

Nikita Gupta, PhD, is a professor in the Department of Electrical Engineering, University Institute of Technology, Himachal Pradesh University, India. She earned her PhD from the Department of Electrical Engineering at Delhi Technological University, Delhi, India, in 2018. She has received multiple awards for her research and is a reviewer of various international conferences and scientific journals.

Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, K L Deemed To Be University, Vijayawada, Andhra Pradesh, India. He completed his post doc from Pentagram Pvt. Ltd. in August 2021. He has six patents to his credit, with several others pending.

Subho Upadhyay, PhD, is a faculty member at Dayalbagh Educational Institute, Agra, India. He earned his PhD from the Indian Institute of Technology, Roorkee, India in August 2017. He has published a number of research papers in various journals and conferences and is a reviewer for various international scientific journals and conferences.

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Table of Contents
Preface
1. Importance of Hybrid Energy System in Reducing Greenhouse Emissions
Rupan Das, Somudeep Bhattacharjee and Uttara Das
1.1 Introduction
1.2 Scenario of Climate Change in the World
1.3 Role of a Hybrid Framework Based on Renewable Energy
1.4 Proposed Model Description
1.5 Mathematical Model of Hybrid System
1.5.1 Solar PV System
1.5.2 Wind Energy System
1.5.3 Diesel Generator
1.5.4 Renewable Voltage Stabilizing Controller
1.5.5 Inverter
1.6 Simulation Model of the Hybrid Energy System
1.6.1 Solar PV System Simulation
1.6.2 Wind Energy System Simulation
1.6.3 Diesel Generator Simulation
1.6.4 Renewable Voltage Stabilizing Controller Simulation
1.7 Results of Simulation Analysis
1.7.1 Hybrid Renewable Energy System Simulation Results
1.7.2 Solar PV Simulation Results
1.7.3 Wind Generation System Simulation Results
1.7.4 Inverter Simulation Result
1.8 Conclusion and Discussion
1.9 Acknowledgments
References
2. Experimental Study on Tilt Angle and Orientation of Rooftop PV Modules for Maximising Power Output for Chandigarh, India
Tarlochan Kaur, Isha Arora, Jaimala Gambhir, Ravneet Kaur and Ayush Gera
2.1 Introduction
2.2 Literature Review
2.3 Experimental Setup
2.3.1 Location Under Study
2.3.2 Experimental Setup
2.3.3 Methodology Used
2.4 Experimental Results and Discussion
2.4.1 Orientation Optimisation of PV Modules
2.4.2 Tilt Angle Optimisation of PV Modules
2.4.2.1 Absolute Maximum Monthly Energy Values Method
2.4.2.2 Weighted Frequency Count (WFC) Method
2.4.2.3 Weighted Maximum Energy (WME) Method
2.4.3 Mutual Shading of PV Modules on Account of Row Spacing
2.5 Latitude and Optimal Tilt Angle
2.6 Conclusions and Future Scope
Acknowledgment
References
3. Biodiesel, Challenges and Solutions
Mukesh Kumar and Mahendra Pal Sharma
3.1 Introduction
3.2 Significant Challenges Faced by Biodiesel
3.2.1 Low Oil Yields and Slow Growth Rate
3.2.2 Selection of Potential Feedstocks
3.3 Conversion of Microalgae into Biodiesel
3.3.1 Transesterification
3.3.2 Direct (In Situ) Transesterification
3.4 Microalgae Biodiesel
3.5 Conclusion
References
4. Comparative Overview of a Novel Configuration of a DC-AC Converter with Reduced Components
Himanshu Sharm, Kamaldeep and Rahul Dogra
4.1 Introduction
4.2 The Novel Topology
4.2.1 State of Operation of the Proposed Inverter
4.2.1.1 First Operating Mode
4.2.1.2 Second Operating Mode
4.2.1.3 Third Operating Mode
4.2.2 Boost Factor Calculation
4.2.3 RMS Value of the Output Voltage
4.3 Performance Characteristics
4.3.1 Boost Factor and Shoot-Through Duty Ratio Variation
4.3.2 Output Voltage Variation with Shoot-Through Duty Ratio
4.3.3 Boost Factor and THD Variation
4.3.4 Capacitor Voltage Stress
4.4 Modulation Technique
4.5 Simulation Results
4.5.1 Simulation Results with MATLAB
4.5.2 Simulation Results with Real-Time Simulator
4.6 Critical Analysis of Proposed Topology with the Conventional Z-Source Inverter
4.7 Conclusion
References
5. Intelligent Sliding Mode Controller for Wind Energy Powered DC Nanogrid
Saurabh Kumar, Vijayakumar K., Ashok Bhupathi Kumar Mukkapati and Rajvir Kaur
5.1 Introduction
5.2 Overview of Wind Energy Conversion System
5.3 System Description
5.4 Controller Description
5.4.1 Particle Swarm Optimization
5.5 Results and Analysis
5.5.1 Comparative Study
5.6 Conclusion
References
6. Grid Integration of Renewable Energy Systems
Pallavi Verma, Rachana Garg and Priya Mahajan
6.1 Introduction
6.2 Modelling of Grid-Interconnected Solar PV System
6.2.1 SPV System
6.2.2 DC-DC Converter
6.2.3 PV Inverter
6.3 Design of Grid-Interconnected Solar PV System
6.3.1 Design of Solar PV Array
6.3.2 Inductor for Boost Converter (Lb)
6.3.3 Selection of Diode and IGBT for Boost Converter
6.3.4 Choice of DC-Link Voltage (Vdc)
6.3.5 Sizing of DC-Link Capacitor (Cdc)
6.3.6 Interfacing Inductors (Lr)
6.4 PV Inverter Control Techniques
6.4.1 Synchronous Reference Frame Theory
6.4.2 Unit Template-Based Control Algorithm
6.4.3 Fuzzy Logic Control (FLC) Algorithm
6.4.3.1 Fuzzification
6.4.3.2 Inference Process
6.4.3.3 Defuzzification
6.4.4 LMS-Based Adaptive Control Algorithm
6.5 MATLAB/Simulink Results and Discussion
6.5.1 Linear/Non-Linear Load Under Steady-State Condition
6.5.2 Linear/Non-Linear Load Under Dynamic Condition
6.5.3 Linear/Non-Linear Load with Change in Irradiation
6.5.4 Linear/Non-Linear Unbalanced Loading Condition
6.5.5 Comparison of LMS-Based Adaptive Control Algorithm with Other Control Algorithms in Terms of Total Harmonics Distortion (THD)
6.6 Conclusion
Appendix
References
7. Modeling and Analysis of Autonomous Hybrid Green Microgrid System for the Electrification of Rural Area
Sumit Sharma, Yog Raj Sood, Ankur Maheshwari and Pallav
7.1 Introduction
7.2 Renewable Energy Technologies
7.3 Economic Evaluation
7.4 Microgrid Protection
7.5 Simulation Results and Discussion
7.5.1 MIC – A: SPV/Wind/Biomass Generator/Hydro/Battery/Converter
7.5.2 MIC – B: SPV/Wind/Diesel Generator/Hydro/Battery/Converter
7.6 Conclusion
References
8. Performance Optimization of a Pine Oil-Fueled Agricultural Engine Using Grey – Taguchi Approach
Rajesh Kumar, Manoj Gwalwanshi, Vikas Verma, Rahul Tarodiya and Manoj Kumar
8.1 Introduction
8.1.1 Taguchi Method
8.1.2 Grey Relational Analysis
8.2 Experimental Setup and Procedure
8.2.1 Experimental Setup
8.2.2 Error Analysis
8.3 Grey-Taguchi Analysis
8.4 Taguchi – SN Ratio
8.4.1 Analysis of Variance (ANOVA)
8.4.2 Confirmatory Experiments
8.5 Results and Discussion
8.6 Conclusion
Acknowledgment
References
9. Nonlinear Mathematical Modeling and Energy Optimization of Multiple-Stage Evaporator Amalgamated with Thermo-Vapor Compressor
Smitarani Pati, Om Prakash Verma, Varun Sharma and Tarun Kumar Sharma
9.1 Introduction
9.2 Process Description
9.3 Nonlinear Energy Modeling
9.3.1 Material Balance Equations
9.3.2 Energy Balance Equations
9.3.3 Thermo-Vapor Compressor (TVC)
9.4 Formulation of the Objective Function
9.5 Solution Approach
9.6 Result and Discussion
9.7 Validity of the Proposed Model
9.8 Conclusion
References
10. Fuel Cell Fed Shunt Active Power Filter for Power Quality Issue by Electric Vehicle Charging
Ravinder Kumar and Hari Om Bansal
10.1 Introduction
10.2 Specification of the Fuel Cell Integrated SAPF
10.2.1 Proton Exchange Membrane Fuel Cell
10.3 Reference Current Generation
10.3.1 ANFIS-Based Control Algorithm
10.4 Discussion and Simulation Findings
10.5 Results and Discussion in Real Time
10.6 Conclusions
References
11. In-Depth Analysis of Various Aspects of Charging Station Infrastructure for Electric Vehicle
Shubham Mishra, Shrey Verma, Gaurav Dwivedi and Subho Upadhyay
11.1 Introduction
11.2 Classification of Electric Vehicles
11.2.1 Hybrid Electric Vehicles (HEVs)
11.2.2 Plug-In Electric Vehicles (PEVs)
11.2.3 Fuel Cell Electric Vehicles (FCEVs)
11.3 Energy Storage Technologies Used in EVs
11.3.1 Battery
11.3.2 Super Capacitor (SC)
11.3.3 Flywheel
11.3.4 Hydrogen Storage
11.4 Types of Electric Vehicle Charging Station (EVCS)
11.5 Aspects and Challenges in the Development of EV Charging Infrastructure
11.5.1 Determining the Optimal Location for Establishing Ev Charging Stations
11.5.2 Ensuring an Optimized and Well-Planned Operation Management
11.5.3 Reducing EV Charging Time by Establishment of High-Class Charging Techniques and Battery Swapping Method
11.5.4 Strategically Handling the Queues of EVs at the Charging Station
11.5.5 Establishing a Promising Structure for Integration with Grid
11.5.6 A Proper Communication Channel for Managing the Grid Operation
11.5.7 Impact on the Environment by EV Charging Station Infrastructure
11.5.8 Impact on Power System Expansion by an Increased Rate of EV Adoption
11.5.9 Proper Sizing of Energy Storage Technologies
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
11.5.11 Use of Energy Storage Technologies and Charging Techniques to Enhance Stability
11.5.12 Determining the Peak Hours for Managing the Charging Load Demand on the Grid for Stable Operation
11.5.13 Estimating a Customer-Friendly as well as Profit-Making Charging Rate
11.6 Developments in the Sector of Electric Vehicles and its Charging Stations in India
11.7 Conclusion
References
12. Optimization of PV Electrolyzer for Hydrogen Production
Sudipta Saikia, Vikas Verma, Sivasakthivel Thangavel, Rahul Tarodiya and Rajesh Kumar
12.1 Introduction
12.2 Hydrogen as a Potential Fuel for the Future
12.3 Properties of Hydrogen
12.4 Fundamental Concepts of Hydrogen Production Processes
12.4.1 Water Electrolysis – Thermodynamic Reactions
12.4.2 Factors Impacting the Rate of Efficiency of Water Electrolysis
12.4.3 Classification of Electrolyzers
12.4.4 Selection Criterion of Electrodes
12.4.5 Effects of Changing Operating Parameters, Sizes and Electrolytic Concentration
12.5 System Description and Components
12.6 Electrochemical Equations
12.7 Methodology
12.7.1 Taguchi Technique
12.7.2 Taguchi – Design of Experiments
12.7.3 Steps of Taguchi Technique
12.8 Results and Discussion
12.8.1 Taguchi Process – Operating Factors for the Perforated Electrolyzer
12.8.2 Taguchi Process – Result of Signal-to-Noise (S/N) Ratio
12.8.3 Taguchi Process – Analysis of Variance (ANOVA)
12.8.4 Confirmation Test
Conclusions
References
13. Assessment of GAMS in Power Network Applications Including Wind Renewable Energy Source
Vineet Kumar, R. Naresh, Veena Sharma and Vineet Kumar
13.1 Introduction
13.1.1 General Background and Motivation
13.1.2 Goal and Challenging Focus
13.2 Importance and a User’s View on GAMS Software
13.2.1 Models for Academic Research
13.2.2 Models for Domain Expert
13.2.3 Black Box Models
13.3 The Basic Structure in the GAMS Environment
13.3.1 Input Command
13.3.2 Output Command
13.4 Power System Applications Using GAMS Software
13.4.1 Multi-Area Economic Dispatch (ED)
13.4.2 AC Optimal Power Flow
13.5 Development Trends in GAMS
13.6 Conclusion
Acknowledgments
References
14. Multi-Objective Design of Fractional Order Robust Controllers for Load Frequency Control
Nitish Katal and Sanjay Kumar Singh
14.1 Introduction
14.2 Mathematical Model of Single Area Load Frequency Control
14.3 Background
14.3.1 Fractional-Order PID Controllers
14.3.2 Multiverse Optimizer
14.4 Proposed Method to Tune PID Controller
14.4.1 Formulation of Optimization Problem
14.4.1.1 Formulation of Objective Function Related to Time-Domain Response
14.4.1.2 Formulation of Objective Function Related to Robust Control
14.5 Results and Discussions
14.5.1 Optimal Controller Synthesis Using Time Domain Approaches
14.5.2 Optimal Robust Controller Synthesis
14.6 Frequency Deviation for 0.02 p.u. Load Change
14.7 Conclusions
Nomenclature
References
15. Challenges and Remedies of Grid-Integrated Renewable Energy Resources
Subho Upadhyay and Ashwini Kumar Nayak
15.1 Introduction
15.2 Developing a Cost-Effective and Adequate Stand-Alone or Grid-Connected Generation System in a Hilly Area
15.3 Challenges of Grid-Connected Hybrid Energy System
15.4 Energy Management
15.4.1 Cycle Charging Strategy
15.4.2 Load Following Strategy
15.4.3 Peak Shaving Strategy
15.5 Frequency Deviation
15.6 Voltage Deviation
15.7 Adequacy Assessment of Intermittent Sources
15.7.1 Failure Rate of PV System
15.7.1.1 Configuration of PV Plant
15.7.1.2 Calculation of Forced Outage Rate of Solar PV System
15.7.2 Failure Rate of Wind System
15.7.2.1 WTG Output as a Function of Wind Speed
15.7.2.2 Determination of DAFOR Using Apportioning Method
15.7.2.3 Reducing Multistate WECS Using the Apportioning Method
15.7.3 Power System Planning
15.8 Conclusion
References
16. Solar Radiations Prediction Model Using Most Influential Climatic Parameters for Selected Indian Cities
Anand Mohan and Gopal Singh
16.1 Introduction
16.2 Introduction to Solar Energy
16.3 Energy Status
16.3.1 World Energy Status
16.3.2 India Energy Status
16.3.3 Himachal Pradesh Energy Status
16.4 Existing Solar Technologies
16.4.1 Solar Thermoelectric Technology
16.4.2 Photovoltaic Technology
16.4.2.1 High Efficiency
16.4.2.2 Thin Films
16.4.2.3 Organic and Dye-Sensitised
16.5 Existing Solar Modeling Techniques
16.5.1 Angstrom Model
16.5.2 Angstrom-Prescott Model
16.5.3 Lieu and Jordan Model
16.6 Relevance for Solar Electrification in Himachal Pradesh
16.7 Literature Review
16.7.1 Related Researches
16.7.2 Gaps in Research Drawn from Literature
16.7.3 Estimation of Solar Radiation Potential
16.7.4 Objectives of the Research
16.8 Methodology Used
16.8.1 Prediction Model Developed Using Artificial Neural Networks
16.8.2 Potential Assessment Using ANN
16.8.3 Identification of Most Influential Parameters
16.8.4 Artificial Neural Network – A Better Prediction Tool
16.8.5 Artificial Neural Networks vs. Regression
16.9 Prediction Model Using Adaptive Neuro-Fuzzy Inference System (ANFIS)
16.9.1 Potential Assessment Using ANFIS
16.10 Different Input Variables
16.10.1 Most Relevant Input Data Selection
16.10.2 Development of a Database for Different Models
16.10.3 Designing of Different Models
16.10.4 Calculation of Maximum Absolute Percentage Error
16.10.5 Selection of Most Suitable Models
16.11 Prediction Model for Ten Selected Cities of Himachal Pradesh
16.11.1 Selection of Input Variables Used for Prediction Model Using ANN
16.11.2 ANN Dependent Solar Radiation Estimation Models
16.12 Sensitivity Test and Error Evaluation of SRPM Models
16.13 Results and Discussion of ANN Model
16.14 Selection of Inputs Used for Prediction Model Using ANFIS
16.15 ANFIS-Based Solar Radiation Prediction Models
16.16 Results and Discussion of ANFIS Model
References
17. Quality Improvement by Eliminating Harmonic Using Nature-Based Optimization Technique
Kamaldeep, Himanshu Sharma, Sanjay Kumar, Arjun Tyagi and Rahul Dogra
17.1 Introduction
17.2 Cascaded H-Bridge Multilevel Inverter
17.3 Harmonic Elimination
17.4 Particle Swarm Optimization (PSO)
17.5 Simulation Results
17.6 Conclusion
References
18. Effect of Degradations and Their Possible Outcomes in PV Cells
Neha Kumari, Sanjay Kumar Singh and Sanjay Kumar
18.1 Introduction
18.1.1 Photovoltaic Cells – An Approach to a Greener World
18.2 Basics of Photovoltaic Cell
18.2.1 History of Semiconductors
18.2.2 Basics of Semiconductors
18.2.3 Photovoltaic Effect
18.2.4 Photovoltaic Cell Efficiency
18.3 Photovoltaic Technology
18.3.1 First-Generation Technology – Photovoltaic Cells Based on Crystalline Silicon Wafer
18.3.1.1 Monocrystalline Silicon Solar Cells (mc-Si)
18.3.1.2 Polycrystalline Silicon Solar Cells (pc-Si)
18.3.1.3 Heterojunction Solar Cells (HIT)
18.3.1.4 PERC Solar Cells
18.3.2 Second-Generation Technology – Photovoltaic Cells Based on Thin Films
18.3.2.1 Amorphous Silicon Solar Cells (a-Si)
18.3.2.2 Cadmium Telluride Solar Cells (CdTe)
18.3.2.3 Copper Indium Gallium Selenium Solar Cells (CIGS)
18.3.3 Third-Generation Technology – Photovoltaic Cells Based on Innovative Technology
18.3.3.1 Organic Solar Cells
18.3.4 Emerging Technologies
18.4 Degradation in Photovoltaics
18.4.1 What is Degradation?
18.4.2 Types of Degradation in Photovoltaic Cells and Its Consequences
18.4.2.1 Hotspots
18.4.2.2 Mechanical Stressing and Cracks
18.4.3 Other Types of Degradations
18.4.3.1 Corrosion
18.4.3.2 Delamination in Photovoltaic Module
18.4.3.3 Discoloration in Photovoltaic Module
18.4.3.4 Potential Induced Degradation (PID)
18.4.3.5 Light-Induced Degradation (LID)
18.4.3.6 Interconnection Degradation
18.4.3.7 Packaging Material Degradation
18.4.3.8 Snail Trails
18.5 Current Status and Challenges in Photovoltaic Technologies
18.5.1 Crystalline Silicon Photovoltaic Cells
18.5.1.1 Current Status and Degradation Level
18.5.1.2 Challenges
18.5.2 Thin-Film Photovoltaic Cells
18.5.2.1 Current Status and Degradation Level
18.5.2.2 Challenges
18.5.3 The Innovative Technology
18.5.3.1 Current Status and Degradation Level
18.5.3.2 Challenges
18.6 Cost and Efficiency Trends in Photovoltaics Over the Past Decade
18.7 Impedance Spectroscopy (IS) – Technique to Identify Degradations in Photovoltaics
18.7.1 AC Equivalent Model of Solar Cell
18.7.2 Impedance Spectroscopy
18.7.3 Procedure for Impedance Spectroscopy
18.8 Conclusion
References
Index

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