Integrated Green Energy Solutions, Volume 2
1. Edition June 2023
384 Pages, Hardcover
Wiley & Sons Ltd
INTEGRATED GREEN ENERGY SOLUTIONS
This second volume in a two-volume set continues to present the state of the art for the concepts, practical applications, and future of renewable energy and how to move closer to true sustainability.
Renewable energy supplies are of ever-increasing environmental and economic importance in every country in the world. A wide range of renewable energy technologies has been established commercially and recognized as an important set of growth industries for most governments. World agencies, such as the United Nations, have extensive programs to encourage these emerging technologies.
This book will bridge the gap between descriptive reviews and specialized engineering technologies. It centers on demonstrating how fundamental physical processes govern renewable energy resources and their applications. Although the applications are being updated continually, the fundamental principles remain the same, and this book will provide a useful platform for those advancing the subject and its industries.
Integrated Resilient Energy Solutions is a two-volume set covering subjects of proven technical and economic importance worldwide. Energy supply from renewables is an essential component of every nation's strategy, especially when there is responsibility for the environment and sustainability. These two volumes will consider the timeless renewable energy technologies' principles yet demonstrate modern applications and case studies. Whether for the veteran engineer, student, or other professional, these two volumes are a must-have for any library.
23 Energy Economics and Environment 1
P. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh Nikokar
Abbreviations 1
23.1 Introduction 2
23.1.1 The Concept of Microgrids 3
23.2 Benefits and Drawbacks of Microgrids 4
23.3 Causes of Increase in Power Plants 6
23.4 Demand Side Management in Microgrids 6
23.5 Centralized Control of Smart Grid 8
23.6 Decentralized Smart Grid Control 9
23.7 DER Resource Control Strategies in the Smart Grid 10
23.8 DER Participation Strategy in Smart Grid 11
23.9 Topics Raised in the Smart Grid 12
23.10 Smart Grid Protection 12
23.11 Detection of Smart Grid Islands 12
23.12 Smart Grid Optimization 13
23.13 Power Quality 13
23.14 Frequency and Voltage Control 13
23.15 Balance between Production and Power Consumption 14
23.16 Ability to Easily Connect Distributed Generation Sources 14
23.17 Smart Network Security 14
23.18 Resynchronization after Network Connection 15
23.19 Smart Grid Control Glasses 15
23.20 Economic Dimensions 15
23.21 Losses 17
23.22 Non-Technical Network Losses 18
23.23 Power System Loss Analysis 19
23.24 The Impact of the Electricity Market on the Performance of Distribution Companies 19
23.25 Power Quality in the Restructured Electricity Market 20
23.26 Conclusion 20
References 21
24 Stringent Energy Management Strategy during Covid-19 Pandemic 25
Nagajayanthi B.
24.1 Introduction 26
24.2 Energy Management 26
24.3 Smart Grid Design 27
24.3.1 Ground Station 27
24.3.2 Gateway 27
24.3.3 Cloud 29
24.4 Smart Grid Design and Testing 31
24.5 Implementation of Smart Grid 35
24.6 Energy Management to Check Overload Conditions 37
24.6.1 With Varying Input Voltage and Without Load 38
24.6.2 With Increased Input Voltage but Without Load 40
24.6.3 With Optimum Input Voltage and Load 41
24.7 Features of Smart Grid System 46
24.8 Conclusion and Future Work 47
References 47
25 Energy Management Strategy for Control and Planning 49
Anmol D. Ganer
25.1 Energy Management and Audit 50
25.1.1 Steps for Energy Audit Management 51
25.1.2 How An Energy Audit can be An Effective Energy Management 51
25.1.3 Power Conservation through Energy Audit 51
25.1.4 Study of Energy Management and Audit 52
25.2 The Different Steps of an Energy Management Approach 52
25.2.1 State-Wise Generation Capacity till 2019 53
25.2.2 The Effective Plan should Incorporate Four Basic Steps 54
25.3 Preliminary Technical and Economic 55
25.3.1 Assessment of Synthetic Gas to Fuel and Chemical with Emphasis on the Potential for Biomass Derived Syngas 55
25.3.2 Natural Gas Storage/Co-Fired Retrofit System 56
25.4 Evaluation of Energy-Saving Investments 56
25.4.1 Power Survey - Energy Inspection 57
25.5 Off-Line and On-Line Procedures 58
25.5.1 Concept 58
25.6 Personnel Training 59
25.6.1 Training Method for Electricity Work Safety 60
25.7 A Successful Energy Management Program 60
25.7.1 Introduction 60
25.7.2 Power Administration Project 60
25.7.3 Corporate Structure 61
25.7.4 Energy Management Managers 61
25.8 Centralize Control of Process and Facility Plants 62
25.8.1 Centralized and Decentralized Waste Water Management 62
25.8.2 Central Jurisdiction System 63
25.8.3 Centralized Process Control System 63
25.9 Energy Security 63
25.9.1 Energy Security Concept 63
25.9.2 Smart Grid Security 65
25.10 Evaluate Energy Performances 65
25.10.1 Concept 65
25.10.2 Building Energy Performance 65
25.10.3 Illumination and Energy Performance 65
25.10.4 Energy Performance of Water Chillers 66
25.11 Energy Action Planning 66
25.12 Energy Economics 67
25.13 Case Study 67
References 68
26 Day-Ahead Solar Power Forecasting Using Statistical and Machine Learning Methods 71
Aadyasha Patel and O.V. Gnana Swathika
Abbreviations 72
26.1 Introduction 74
26.2 Durations of Forecasting 76
26.3 Forecasting Techniques 77
26.4 Statistical Methods 83
26.4.1 Grey-Box Model (GB) 83
26.4.2 Grey Theory (GT) 83
26.4.3 Markov Chain Model (MM) 83
26.4.4 Bayesian Optimization 83
26.4.5 Linear Pool Ensemble (LPE) 84
26.4.6 Variational Mode Decomposition (VMD) 84
26.4.7 Autoregressive Integrated Moving Average (ARIMA) 84
26.4.8 Quantile Regression Averaging (QRA) 84
26.4.9 Logistic Model Trees 84
26.4.10 k-Nearest Neighbours (kNN) 85
26.5 Machine Learning Techniques 85
26.5.1 Machine Learning (ML) 85
26.5.2 Automatic Machine Learning (AML) 85
26.5.3 Extreme Learning Machine (ELM) 85
26.5.4 Quantile Random Forest (QRF) 86
26.5.5 Support Vector Regression (SVR) 86
26.5.6 Least-Square Support Vector Machine (LSSVM) 86
26.5.7 Principal Component Analysis (PCA) 86
26.5.8 Hierarchical Similarity-Based Forecasting Model (hSBFM) 87
26.5.9 Local Sensitive Hashing Algorithm (LSH) 87
26.6 Deep Learning (DL) 87
26.6.1 Artificial Neural Network (ANN) 87
26.6.2 Feed Forward Neural Network (FFNN) 87
26.6.3 Convolutional Neural Network (CNN) 88
26.6.4 Elman-Based Neural Network (ENN) 88
26.6.5 Deep Belief Network (DBN) 88
26.6.6 Long Short-Term Memory (LSTM) 88
26.6.7 Autoencoder Long Short-Term Memory (AE-LSTM) 89
26.6.8 Self-Organizing Maps (SOM) 89
26.7 Evaluation Index and Metrics 89
26.8 Conclusions 96
References 97
27 A Review on Optimum Location and Sizing of DGs in Radial Distribution System 103
P. Tejaswi and O.V. Gnana Swathika
Abbreviations 103
27.1 Introduction 104
27.1.1 DG Planning Based on Multi-Objective Optimization Techniques 108
27.1.2 Optimal Placement and Sizing of DG Based on Multi-Objective Optimization Techniques 110
27.2 Proposed Location and Sizing of DGs in RDS Using Analytical and PSO Methods 114
27.2.1 Methodology 114
27.2.1.1 Distribution Load Flow Solution 114
27.2.1.2 Multiple DG Allocation and DG Size 116
27.2.1.3 PSO Algorithm 118
27.2.2 Multi-Objective Function 119
27.3 Result 120
27.4 Conclusion 123
27.5 Appendix: List of Symbols 124
References 124
28 High Step Up Non-Isolated DC-DC Converter Using Active-Passive Inductor Cells 133
Kanimozhi, G., Amritha, G. and O.V. Gnana Swathika
28.1 Introduction 133
28.2 Proposed Converter 135
28.2.1 Features of the Suggested Converter 136
28.3 Modes of Operation 137
28.4 Design Considerations 140
28.5 Simulation 142
28.5.1 Simulation for n= 1 143
28.5.2 Simulation Results for n= 2 144
28.6 Hardware Results 144
28.7 Conclusion 148
References 149
29 A Non-Isolated Step-Up Quasi Z-Source Converter Using Coupled Inductor 151
Shashank, P.C. and Kanimozhi, G.
29.1 Introduction 151
29.2 Improved Quasi Z Source Converter with Coupled Inductor 154
29.3 Modes of Operation 154
29.4 Simulation Results 158
29.5 Comparison 163
29.6 Conclusion 165
References 165
30 Datalogger Aided Stand-Alone PV System for Rural Electrification 167
Aashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana Swathika
Abbreviations and Nomenclature 168
30.1 Introduction 169
30.1.1 Motivation 169
30.1.2 Objectives 170
30.2 Work Description 170
30.2.1 Overview of the Work 170
30.2.2 Literature Review 170
30.2.3 Methodologies 172
30.2.4 Optimization Techniques 174
30.2.5 IoT and Smart Technologies 175
30.2.6 Conclusion 177
30.3 Design and Realisation of dl 177
30.3.1 dl Description 177
30.3.2 Solar Panel 177
30.3.3 Arduino Uno and IDE 179
30.3.4 Voltage Sensor 180
30.3.5 Current Sensor 182
30.3.6 PLX-DAQ Data Acquisition Tool 184
30.3.7 Software Specifications 186
30.3.8 Methodology 186
30.3.8.1 Data Logging into Excel Macro Spreadsheet 187
30.3.8.2 Prediction Using Mathematical Model 188
30.4 Results 190
30.4.1 Prediction Results 190
30.4.2 Performance Metrics 192
30.4.2.1 Mape 192
30.5 Conclusion 196
30.5.1 Cost Calculation 196
30.5.2 Scope of Work 196
30.5.3 Summary 196
References 197
31 Working and Analysis of an Electromagnet-Based DC V-Gate Magnet Motor for Electrical Applications 201
G. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja
31.1 Conceptual Introduction 202
31.2 Existing Technologies to Review 203
31.3 Proposed Design 204
31.4 Block Schematic 205
31.5 Motor Assembly and Control Structure 206
31.6 Control Operation of the V-Gate Magnet Motor 207
31.7 Results and Analysis 208
31.8 Conclusion and Further Scope of Research 213
References 214
32 Design and Realization of Smart and Energy-Efficient Doorbell 217
Shubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.
32.1 Introduction 218
32.2 Methodology 218
32.3 Design and Specification 219
32.3.1 Software-Based Approach 219
32.3.1.1 Component Used 220
32.3.1.2 Circuit Diagram 221
32.3.2 Hardware-Based Approach 221
32.3.2.1 Components Used 222
32.3.2.2 Circuit Diagram 223
32.4 Result and Discussion 224
32.5 Conclusion 228
References 229
33 Optimal Solar Charging Enabled Autonomous Cleaning Robot 231
Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
33.1 Introduction 231
33.2 Methodology 233
33.2.1 Design Specification 233
33.2.2 Trash Detection 236
33.2.3 Movement Algorithm 238
33.2.4 Solar Charging 241
33.2.5 Remote Monitoring 242
33.3 Results 243
33.3.1 Trash Detection Results 243
33.3.2 Solar Charging Results 245
33.3.3 Remote Monitoring Dashboard 245
33.4 Conclusion 246
References 246
34 Real-Time Health Monitoring System of a Distribution Transformer 249
Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
34.1 Introduction 249
34.2 Flow Diagram 250
34.3 Operating Principle 250
34.4 Observation and Result 252
34.5 IFTTT Email Notification (in case of a fault) 253
34.6 Conclusion 253
References 253
35 Analysis of Wide-Angle Polarization-Insensitive Metamaterial Absorber Using Equivalent Circuit Modeling for Energy Harvesting Application 255
Kanwar Preet Kaur and Trushit Upadhyaya
35.1 Introduction 255
35.2 Absorber Theory and Proposed Unit Cell Design 257
35.3 Equivalent Circuit Model 258
35.4 Simulation Results 260
35.4.1 Retrieval of the Effective MMA Parameters 261
35.4.2 Absorption Mechanism 262
35.4.3 Polarization Angle and Oblique Angle Variations 262
35.4.4 Resistive Load Variations 262
35.5 Experimental Results 268
35.6 Conclusion 270
References 271
36 World Energy Demand 275
Satish R. Billewar, Gaurav Londhe and Pradip Suresh Mane
36.1 Energy End Users 276
36.2 Rural Electrification 281
36.3 Residential and Non-Residential Buildings 282
36.3.1 Urban and Semi-Urban Zones Power Requirement 283
36.3.2 Rural Residential Requirements 284
36.3.3 Non Residential Buildings 284
36.4 Industry 286
36.4.1 Industrialization, the Environment, and Pollution 287
36.4.2 Green Industry Initiative 292
36.5 Transport 294
36.5.1 The United Nations Environment Programme (unep) 294
36.5.2 The Initiatives of Countries 295
36.5.3 Sustainable Development Goals (SDGs) 296
36.5.4 Economic Sector Initiatives 299
36.5.5 Social Sector Initiatives 300
36.5.6 Environmental Sector Initiatives 300
36.5.7 The ASI Approach 301
36.6 Agriculture 302
36.6.1 Soil Fertility and Irrigation 305
36.6.2 Pesticides and Biomass Pollution Control 305
36.6.3 Agroforestry 307
36.6.4 Biotechnologies 308
36.7 Performance Mapping in Conjunction with Technological Evolution 310
References 315
37 Education in Energy Conversion and Management 317
Satish R. Billewar, Karuna Jadhav and Gaurav Londhe
37.1 Role of University 318
37.2 Personnel Training 319
37.3 Awareness of Energy Conversion and Management as an Intersectoral Discipline 320
37.4 Climate Change 321
37.5 Economic Policy Options 326
37.6 Policy in Practice 328
37.7 Green Economy 330
37.8 The Relationship between the Economy and the Environment 332
37.8.1 Assessing Pollution's Environmental Impact 334
37.8.2 Ecosystem Recovery and Rehabilitation 335
37.8.3 Sustainable Development Ideology 338
37.9 Industrial Ecology 338
37.9.1 Ecosystem's Health and Adaptability 340
37.10 Does Protecting the Environment Harm the Economy? 343
37.10.1 Market and Accounting Mechanism 344
37.10.2 UN Environment Program (UNEP) 345
37.11 Creating a Green Economy 346
37.11.1 Green Project Financing 347
37.11.2 Natural Capital Sustainably 348
37.11.3 Partnerships 349
37.11.4 Educational Sustainability 349
37.11.5 Environment Friendly Technologies 350
References 351
About the Editors 353
Index 355
W. S. Sampath, PhD, is a professor in the Department of Mechanical Engineering, Colorado State University, Director for Next Generation Photovoltaics (NGPV) Laboratory at Colorado State University, and Site Director at NSF I/UCRC for Next Generation Photovoltaics. With over 30 years of industry experience, he has contributed significantly to the science of renewable energy.
O. V. Gnana Swathika, PhD, is an associate professor in the School of Electrical Engineering at VIT Chennai, India. She earned her PhD in electrical engineering at VIT University and completed her postdoc at the University of Moratuwa, Sri Lanka.
Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway. He received his PhD in electrical engineering from the University of Bologna, Italy. He has almost ten years of teaching, research, and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching. He is currently involved in publishing multiple books with Wiley-Scrivener.