Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. 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.

• Preface xv23 Energy Economics and Environment 1P. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh NikokarAbbreviations 123.1 Introduction 223.1.1 The Concept of Microgrids 323.2 Benefits and Drawbacks of Microgrids 423.3 Causes of Increase in Power Plants 623.4 Demand Side Management in Microgrids 623.5 Centralized Control of Smart Grid 823.6 Decentralized Smart Grid Control 923.7 DER Resource Control Strategies in the Smart Grid 1023.8 DER Participation Strategy in Smart Grid 1123.9 Topics Raised in the Smart Grid 1223.10 Smart Grid Protection 1223.11 Detection of Smart Grid Islands 1223.12 Smart Grid Optimization 1323.13 Power Quality 1323.14 Frequency and Voltage Control 1323.15 Balance between Production and Power Consumption 1423.16 Ability to Easily Connect Distributed Generation Sources 1423.17 Smart Network Security 1423.18 Resynchronization after Network Connection 1523.19 Smart Grid Control Glasses 1523.20 Economic Dimensions 1523.21 Losses 1723.22 Non-Technical Network Losses 1823.23 Power System Loss Analysis 1923.24 The Impact of the Electricity Market on the Performance of Distribution Companies 1923.25 Power Quality in the Restructured Electricity Market 2023.26 Conclusion 20References 2124 Stringent Energy Management Strategy during Covid-19 Pandemic 25Nagajayanthi B.24.1 Introduction 2624.2 Energy Management 2624.3 Smart Grid Design 2724.3.1 Ground Station 2724.3.2 Gateway 2724.3.3 Cloud 2924.4 Smart Grid Design and Testing 3124.5 Implementation of Smart Grid 3524.6 Energy Management to Check Overload Conditions 3724.6.1 With Varying Input Voltage and Without Load 3824.6.2 With Increased Input Voltage but Without Load 4024.6.3 With Optimum Input Voltage and Load 4124.7 Features of Smart Grid System 4624.8 Conclusion and Future Work 47References 4725 Energy Management Strategy for Control and Planning 49Anmol D. Ganer25.1 Energy Management and Audit 5025.1.1 Steps for Energy Audit Management 5125.1.2 How An Energy Audit can be An Effective Energy Management 5125.1.3 Power Conservation through Energy Audit 5125.1.4 Study of Energy Management and Audit 5225.2 The Different Steps of an Energy Management Approach 5225.2.1 State-Wise Generation Capacity till 2019 5325.2.2 The Effective Plan should Incorporate Four Basic Steps 5425.3 Preliminary Technical and Economic 5525.3.1 Assessment of Synthetic Gas to Fuel and Chemical with Emphasis on the Potential for Biomass Derived Syngas 5525.3.2 Natural Gas Storage/Co-Fired Retrofit System 5625.4 Evaluation of Energy-Saving Investments 5625.4.1 Power Survey – Energy Inspection 5725.5 Off-Line and On-Line Procedures 5825.5.1 Concept 5825.6 Personnel Training 5925.6.1 Training Method for Electricity Work Safety 6025.7 A Successful Energy Management Program 6025.7.1 Introduction 6025.7.2 Power Administration Project 6025.7.3 Corporate Structure 6125.7.4 Energy Management Managers 6125.8 Centralize Control of Process and Facility Plants 6225.8.1 Centralized and Decentralized Waste Water Management 6225.8.2 Central Jurisdiction System 6325.8.3 Centralized Process Control System 6325.9 Energy Security 6325.9.1 Energy Security Concept 6325.9.2 Smart Grid Security 6525.10 Evaluate Energy Performances 6525.10.1 Concept 6525.10.2 Building Energy Performance 6525.10.3 Illumination and Energy Performance 6525.10.4 Energy Performance of Water Chillers 6625.11 Energy Action Planning 6625.12 Energy Economics 6725.13 Case Study 67References 6826 Day-Ahead Solar Power Forecasting Using Statistical and Machine Learning Methods 71Aadyasha Patel and O.V. Gnana SwathikaAbbreviations 7226.1 Introduction 7426.2 Durations of Forecasting 7626.3 Forecasting Techniques 7726.4 Statistical Methods 8326.4.1 Grey-Box Model (GB) 8326.4.2 Grey Theory (GT) 8326.4.3 Markov Chain Model (MM) 8326.4.4 Bayesian Optimization 8326.4.5 Linear Pool Ensemble (LPE) 8426.4.6 Variational Mode Decomposition (VMD) 8426.4.7 Autoregressive Integrated Moving Average (ARIMA) 8426.4.8 Quantile Regression Averaging (QRA) 8426.4.9 Logistic Model Trees 8426.4.10 k-Nearest Neighbours (kNN) 8526.5 Machine Learning Techniques 8526.5.1 Machine Learning (ML) 8526.5.2 Automatic Machine Learning (AML) 8526.5.3 Extreme Learning Machine (ELM) 8526.5.4 Quantile Random Forest (QRF) 8626.5.5 Support Vector Regression (SVR) 8626.5.6 Least-Square Support Vector Machine (LSSVM) 8626.5.7 Principal Component Analysis (PCA) 8626.5.8 Hierarchical Similarity-Based Forecasting Model (hSBFM) 8726.5.9 Local Sensitive Hashing Algorithm (LSH) 8726.6 Deep Learning (DL) 8726.6.1 Artificial Neural Network (ANN) 8726.6.2 Feed Forward Neural Network (FFNN) 8726.6.3 Convolutional Neural Network (CNN) 8826.6.4 Elman-Based Neural Network (ENN) 8826.6.5 Deep Belief Network (DBN) 8826.6.6 Long Short-Term Memory (LSTM) 8826.6.7 Autoencoder Long Short-Term Memory (AE-LSTM) 8926.6.8 Self-Organizing Maps (SOM) 8926.7 Evaluation Index and Metrics 8926.8 Conclusions 96References 9727 A Review on Optimum Location and Sizing of DGs in Radial Distribution System 103P. Tejaswi and O.V. Gnana SwathikaAbbreviations 10327.1 Introduction 10427.1.1 DG Planning Based on Multi-Objective Optimization Techniques 10827.1.2 Optimal Placement and Sizing of DG Based on Multi-Objective Optimization Techniques 11027.2 Proposed Location and Sizing of DGs in RDS Using Analytical and PSO Methods 11427.2.1 Methodology 11427.2.1.1 Distribution Load Flow Solution 11427.2.1.2 Multiple DG Allocation and DG Size 11627.2.1.3 PSO Algorithm 11827.2.2 Multi-Objective Function 11927.3 Result 12027.4 Conclusion 12327.5 Appendix: List of Symbols 124References 12428 High Step Up Non-Isolated DC-DC Converter Using Active-Passive Inductor Cells 133Kanimozhi, G., Amritha, G. and O.V. Gnana Swathika28.1 Introduction 13328.2 Proposed Converter 13528.2.1 Features of the Suggested Converter 13628.3 Modes of Operation 13728.4 Design Considerations 14028.5 Simulation 14228.5.1 Simulation for n= 1 14328.5.2 Simulation Results for n= 2 14428.6 Hardware Results 14428.7 Conclusion 148References 14929 A Non-Isolated Step-Up Quasi Z-Source Converter Using Coupled Inductor 151Shashank, P.C. and Kanimozhi, G.29.1 Introduction 15129.2 Improved Quasi Z Source Converter with Coupled Inductor 15429.3 Modes of Operation 15429.4 Simulation Results 15829.5 Comparison 16329.6 Conclusion 165References 16530 Datalogger Aided Stand-Alone PV System for Rural Electrification 167Aashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana SwathikaAbbreviations and Nomenclature 16830.1 Introduction 16930.1.1 Motivation 16930.1.2 Objectives 17030.2 Work Description 17030.2.1 Overview of the Work 17030.2.2 Literature Review 17030.2.3 Methodologies 17230.2.4 Optimization Techniques 17430.2.5 IoT and Smart Technologies 17530.2.6 Conclusion 17730.3 Design and Realisation of dl 17730.3.1 dl Description 17730.3.2 Solar Panel 17730.3.3 Arduino Uno and IDE 17930.3.4 Voltage Sensor 18030.3.5 Current Sensor 18230.3.6 PLX-DAQ Data Acquisition Tool 18430.3.7 Software Specifications 18630.3.8 Methodology 18630.3.8.1 Data Logging into Excel Macro Spreadsheet 18730.3.8.2 Prediction Using Mathematical Model 18830.4 Results 19030.4.1 Prediction Results 19030.4.2 Performance Metrics 19230.4.2.1 Mape 19230.5 Conclusion 19630.5.1 Cost Calculation 19630.5.2 Scope of Work 19630.5.3 Summary 196References 19731 Working and Analysis of an Electromagnet-Based DC V-Gate Magnet Motor for Electrical Applications 201G. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja31.1 Conceptual Introduction 20231.2 Existing Technologies to Review 20331.3 Proposed Design 20431.4 Block Schematic 20531.5 Motor Assembly and Control Structure 20631.6 Control Operation of the V-Gate Magnet Motor 20731.7 Results and Analysis 20831.8 Conclusion and Further Scope of Research 213References 21432 Design and Realization of Smart and Energy-Efficient Doorbell 217Shubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.32.1 Introduction 21832.2 Methodology 21832.3 Design and Specification 21932.3.1 Software-Based Approach 21932.3.1.1 Component Used 22032.3.1.2 Circuit Diagram 22132.3.2 Hardware-Based Approach 22132.3.2.1 Components Used 22232.3.2.2 Circuit Diagram 22332.4 Result and Discussion 22432.5 Conclusion 228References 22933 Optimal Solar Charging Enabled Autonomous Cleaning Robot 231Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika33.1 Introduction 23133.2 Methodology 23333.2.1 Design Specification 23333.2.2 Trash Detection 23633.2.3 Movement Algorithm 23833.2.4 Solar Charging 24133.2.5 Remote Monitoring 24233.3 Results 24333.3.1 Trash Detection Results 24333.3.2 Solar Charging Results 24533.3.3 Remote Monitoring Dashboard 24533.4 Conclusion 246References 24634 Real-Time Health Monitoring System of a Distribution Transformer 249Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika34.1 Introduction 24934.2 Flow Diagram 25034.3 Operating Principle 25034.4 Observation and Result 25234.5 IFTTT Email Notification (in case of a fault) 25334.6 Conclusion 253References 25335 Analysis of Wide-Angle Polarization-Insensitive Metamaterial Absorber Using Equivalent Circuit Modeling for Energy Harvesting Application 255Kanwar Preet Kaur and Trushit Upadhyaya35.1 Introduction 25535.2 Absorber Theory and Proposed Unit Cell Design 25735.3 Equivalent Circuit Model 25835.4 Simulation Results 26035.4.1 Retrieval of the Effective MMA Parameters 26135.4.2 Absorption Mechanism 26235.4.3 Polarization Angle and Oblique Angle Variations 26235.4.4 Resistive Load Variations 26235.5 Experimental Results 26835.6 Conclusion 270References 27136 World Energy Demand 275Satish R. Billewar, Gaurav Londhe and Pradip Suresh Mane36.1 Energy End Users 27636.2 Rural Electrification 28136.3 Residential and Non-Residential Buildings 28236.3.1 Urban and Semi-Urban Zones Power Requirement 28336.3.2 Rural Residential Requirements 28436.3.3 Non Residential Buildings 28436.4 Industry 28636.4.1 Industrialization, the Environment, and Pollution 28736.4.2 Green Industry Initiative 29236.5 Transport 29436.5.1 The United Nations Environment Programme (unep) 29436.5.2 The Initiatives of Countries 29536.5.3 Sustainable Development Goals (SDGs) 29636.5.4 Economic Sector Initiatives 29936.5.5 Social Sector Initiatives 30036.5.6 Environmental Sector Initiatives 30036.5.7 The ASI Approach 30136.6 Agriculture 30236.6.1 Soil Fertility and Irrigation 30536.6.2 Pesticides and Biomass Pollution Control 30536.6.3 Agroforestry 30736.6.4 Biotechnologies 30836.7 Performance Mapping in Conjunction with Technological Evolution 310References 31537 Education in Energy Conversion and Management 317Satish R. Billewar, Karuna Jadhav and Gaurav Londhe37.1 Role of University 31837.2 Personnel Training 31937.3 Awareness of Energy Conversion and Management as an Intersectoral Discipline 32037.4 Climate Change 32137.5 Economic Policy Options 32637.6 Policy in Practice 32837.7 Green Economy 33037.8 The Relationship between the Economy and the Environment 33237.8.1 Assessing Pollution’s Environmental Impact 33437.8.2 Ecosystem Recovery and Rehabilitation 33537.8.3 Sustainable Development Ideology 33837.9 Industrial Ecology 33837.9.1 Ecosystem’s Health and Adaptability 34037.10 Does Protecting the Environment Harm the Economy? 34337.10.1 Market and Accounting Mechanism 34437.10.2 UN Environment Program (UNEP) 34537.11 Creating a Green Economy 34637.11.1 Green Project Financing 34737.11.2 Natural Capital Sustainably 34837.11.3 Partnerships 34937.11.4 Educational Sustainability 34937.11.5 Environment Friendly Technologies 350References 351About the Editors 353Index 355

Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. 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.

• Preface xv23 Energy Economics and Environment 1P. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh NikokarAbbreviations 123.1 Introduction 223.1.1 The Concept of Microgrids 323.2 Benefits and Drawbacks of Microgrids 423.3 Causes of Increase in Power Plants 623.4 Demand Side Management in Microgrids 623.5 Centralized Control of Smart Grid 823.6 Decentralized Smart Grid Control 923.7 DER Resource Control Strategies in the Smart Grid 1023.8 DER Participation Strategy in Smart Grid 1123.9 Topics Raised in the Smart Grid 1223.10 Smart Grid Protection 1223.11 Detection of Smart Grid Islands 1223.12 Smart Grid Optimization 1323.13 Power Quality 1323.14 Frequency and Voltage Control 1323.15 Balance between Production and Power Consumption 1423.16 Ability to Easily Connect Distributed Generation Sources 1423.17 Smart Network Security 1423.18 Resynchronization after Network Connection 1523.19 Smart Grid Control Glasses 1523.20 Economic Dimensions 1523.21 Losses 1723.22 Non-Technical Network Losses 1823.23 Power System Loss Analysis 1923.24 The Impact of the Electricity Market on the Performance of Distribution Companies 1923.25 Power Quality in the Restructured Electricity Market 2023.26 Conclusion 20References 2124 Stringent Energy Management Strategy during Covid-19 Pandemic 25Nagajayanthi B.24.1 Introduction 2624.2 Energy Management 2624.3 Smart Grid Design 2724.3.1 Ground Station 2724.3.2 Gateway 2724.3.3 Cloud 2924.4 Smart Grid Design and Testing 3124.5 Implementation of Smart Grid 3524.6 Energy Management to Check Overload Conditions 3724.6.1 With Varying Input Voltage and Without Load 3824.6.2 With Increased Input Voltage but Without Load 4024.6.3 With Optimum Input Voltage and Load 4124.7 Features of Smart Grid System 4624.8 Conclusion and Future Work 47References 4725 Energy Management Strategy for Control and Planning 49Anmol D. Ganer25.1 Energy Management and Audit 5025.1.1 Steps for Energy Audit Management 5125.1.2 How An Energy Audit can be An Effective Energy Management 5125.1.3 Power Conservation through Energy Audit 5125.1.4 Study of Energy Management and Audit 5225.2 The Different Steps of an Energy Management Approach 5225.2.1 State-Wise Generation Capacity till 2019 5325.2.2 The Effective Plan should Incorporate Four Basic Steps 5425.3 Preliminary Technical and Economic 5525.3.1 Assessment of Synthetic Gas to Fuel and Chemical with Emphasis on the Potential for Biomass Derived Syngas 5525.3.2 Natural Gas Storage/Co-Fired Retrofit System 5625.4 Evaluation of Energy-Saving Investments 5625.4.1 Power Survey – Energy Inspection 5725.5 Off-Line and On-Line Procedures 5825.5.1 Concept 5825.6 Personnel Training 5925.6.1 Training Method for Electricity Work Safety 6025.7 A Successful Energy Management Program 6025.7.1 Introduction 6025.7.2 Power Administration Project 6025.7.3 Corporate Structure 6125.7.4 Energy Management Managers 6125.8 Centralize Control of Process and Facility Plants 6225.8.1 Centralized and Decentralized Waste Water Management 6225.8.2 Central Jurisdiction System 6325.8.3 Centralized Process Control System 6325.9 Energy Security 6325.9.1 Energy Security Concept 6325.9.2 Smart Grid Security 6525.10 Evaluate Energy Performances 6525.10.1 Concept 6525.10.2 Building Energy Performance 6525.10.3 Illumination and Energy Performance 6525.10.4 Energy Performance of Water Chillers 6625.11 Energy Action Planning 6625.12 Energy Economics 6725.13 Case Study 67References 6826 Day-Ahead Solar Power Forecasting Using Statistical and Machine Learning Methods 71Aadyasha Patel and O.V. Gnana SwathikaAbbreviations 7226.1 Introduction 7426.2 Durations of Forecasting 7626.3 Forecasting Techniques 7726.4 Statistical Methods 8326.4.1 Grey-Box Model (GB) 8326.4.2 Grey Theory (GT) 8326.4.3 Markov Chain Model (MM) 8326.4.4 Bayesian Optimization 8326.4.5 Linear Pool Ensemble (LPE) 8426.4.6 Variational Mode Decomposition (VMD) 8426.4.7 Autoregressive Integrated Moving Average (ARIMA) 8426.4.8 Quantile Regression Averaging (QRA) 8426.4.9 Logistic Model Trees 8426.4.10 k-Nearest Neighbours (kNN) 8526.5 Machine Learning Techniques 8526.5.1 Machine Learning (ML) 8526.5.2 Automatic Machine Learning (AML) 8526.5.3 Extreme Learning Machine (ELM) 8526.5.4 Quantile Random Forest (QRF) 8626.5.5 Support Vector Regression (SVR) 8626.5.6 Least-Square Support Vector Machine (LSSVM) 8626.5.7 Principal Component Analysis (PCA) 8626.5.8 Hierarchical Similarity-Based Forecasting Model (hSBFM) 8726.5.9 Local Sensitive Hashing Algorithm (LSH) 8726.6 Deep Learning (DL) 8726.6.1 Artificial Neural Network (ANN) 8726.6.2 Feed Forward Neural Network (FFNN) 8726.6.3 Convolutional Neural Network (CNN) 8826.6.4 Elman-Based Neural Network (ENN) 8826.6.5 Deep Belief Network (DBN) 8826.6.6 Long Short-Term Memory (LSTM) 8826.6.7 Autoencoder Long Short-Term Memory (AE-LSTM) 8926.6.8 Self-Organizing Maps (SOM) 8926.7 Evaluation Index and Metrics 8926.8 Conclusions 96References 9727 A Review on Optimum Location and Sizing of DGs in Radial Distribution System 103P. Tejaswi and O.V. Gnana SwathikaAbbreviations 10327.1 Introduction 10427.1.1 DG Planning Based on Multi-Objective Optimization Techniques 10827.1.2 Optimal Placement and Sizing of DG Based on Multi-Objective Optimization Techniques 11027.2 Proposed Location and Sizing of DGs in RDS Using Analytical and PSO Methods 11427.2.1 Methodology 11427.2.1.1 Distribution Load Flow Solution 11427.2.1.2 Multiple DG Allocation and DG Size 11627.2.1.3 PSO Algorithm 11827.2.2 Multi-Objective Function 11927.3 Result 12027.4 Conclusion 12327.5 Appendix: List of Symbols 124References 12428 High Step Up Non-Isolated DC-DC Converter Using Active-Passive Inductor Cells 133Kanimozhi, G., Amritha, G. and O.V. Gnana Swathika28.1 Introduction 13328.2 Proposed Converter 13528.2.1 Features of the Suggested Converter 13628.3 Modes of Operation 13728.4 Design Considerations 14028.5 Simulation 14228.5.1 Simulation for n= 1 14328.5.2 Simulation Results for n= 2 14428.6 Hardware Results 14428.7 Conclusion 148References 14929 A Non-Isolated Step-Up Quasi Z-Source Converter Using Coupled Inductor 151Shashank, P.C. and Kanimozhi, G.29.1 Introduction 15129.2 Improved Quasi Z Source Converter with Coupled Inductor 15429.3 Modes of Operation 15429.4 Simulation Results 15829.5 Comparison 16329.6 Conclusion 165References 16530 Datalogger Aided Stand-Alone PV System for Rural Electrification 167Aashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana SwathikaAbbreviations and Nomenclature 16830.1 Introduction 16930.1.1 Motivation 16930.1.2 Objectives 17030.2 Work Description 17030.2.1 Overview of the Work 17030.2.2 Literature Review 17030.2.3 Methodologies 17230.2.4 Optimization Techniques 17430.2.5 IoT and Smart Technologies 17530.2.6 Conclusion 17730.3 Design and Realisation of dl 17730.3.1 dl Description 17730.3.2 Solar Panel 17730.3.3 Arduino Uno and IDE 17930.3.4 Voltage Sensor 18030.3.5 Current Sensor 18230.3.6 PLX-DAQ Data Acquisition Tool 18430.3.7 Software Specifications 18630.3.8 Methodology 18630.3.8.1 Data Logging into Excel Macro Spreadsheet 18730.3.8.2 Prediction Using Mathematical Model 18830.4 Results 19030.4.1 Prediction Results 19030.4.2 Performance Metrics 19230.4.2.1 Mape 19230.5 Conclusion 19630.5.1 Cost Calculation 19630.5.2 Scope of Work 19630.5.3 Summary 196References 19731 Working and Analysis of an Electromagnet-Based DC V-Gate Magnet Motor for Electrical Applications 201G. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja31.1 Conceptual Introduction 20231.2 Existing Technologies to Review 20331.3 Proposed Design 20431.4 Block Schematic 20531.5 Motor Assembly and Control Structure 20631.6 Control Operation of the V-Gate Magnet Motor 20731.7 Results and Analysis 20831.8 Conclusion and Further Scope of Research 213References 21432 Design and Realization of Smart and Energy-Efficient Doorbell 217Shubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.32.1 Introduction 21832.2 Methodology 21832.3 Design and Specification 21932.3.1 Software-Based Approach 21932.3.1.1 Component Used 22032.3.1.2 Circuit Diagram 22132.3.2 Hardware-Based Approach 22132.3.2.1 Components Used 22232.3.2.2 Circuit Diagram 22332.4 Result and Discussion 22432.5 Conclusion 228References 22933 Optimal Solar Charging Enabled Autonomous Cleaning Robot 231Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika33.1 Introduction 23133.2 Methodology 23333.2.1 Design Specification 23333.2.2 Trash Detection 23633.2.3 Movement Algorithm 23833.2.4 Solar Charging 24133.2.5 Remote Monitoring 24233.3 Results 24333.3.1 Trash Detection Results 24333.3.2 Solar Charging Results 24533.3.3 Remote Monitoring Dashboard 24533.4 Conclusion 246References 24634 Real-Time Health Monitoring System of a Distribution Transformer 249Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika34.1 Introduction 24934.2 Flow Diagram 25034.3 Operating Principle 25034.4 Observation and Result 25234.5 IFTTT Email Notification (in case of a fault) 25334.6 Conclusion 253References 25335 Analysis of Wide-Angle Polarization-Insensitive Metamaterial Absorber Using Equivalent Circuit Modeling for Energy Harvesting Application 255Kanwar Preet Kaur and Trushit Upadhyaya35.1 Introduction 25535.2 Absorber Theory and Proposed Unit Cell Design 25735.3 Equivalent Circuit Model 25835.4 Simulation Results 26035.4.1 Retrieval of the Effective MMA Parameters 26135.4.2 Absorption Mechanism 26235.4.3 Polarization Angle and Oblique Angle Variations 26235.4.4 Resistive Load Variations 26235.5 Experimental Results 26835.6 Conclusion 270References 27136 World Energy Demand 275Satish R. Billewar, Gaurav Londhe and Pradip Suresh Mane36.1 Energy End Users 27636.2 Rural Electrification 28136.3 Residential and Non-Residential Buildings 28236.3.1 Urban and Semi-Urban Zones Power Requirement 28336.3.2 Rural Residential Requirements 28436.3.3 Non Residential Buildings 28436.4 Industry 28636.4.1 Industrialization, the Environment, and Pollution 28736.4.2 Green Industry Initiative 29236.5 Transport 29436.5.1 The United Nations Environment Programme (unep) 29436.5.2 The Initiatives of Countries 29536.5.3 Sustainable Development Goals (SDGs) 29636.5.4 Economic Sector Initiatives 29936.5.5 Social Sector Initiatives 30036.5.6 Environmental Sector Initiatives 30036.5.7 The ASI Approach 30136.6 Agriculture 30236.6.1 Soil Fertility and Irrigation 30536.6.2 Pesticides and Biomass Pollution Control 30536.6.3 Agroforestry 30736.6.4 Biotechnologies 30836.7 Performance Mapping in Conjunction with Technological Evolution 310References 31537 Education in Energy Conversion and Management 317Satish R. Billewar, Karuna Jadhav and Gaurav Londhe37.1 Role of University 31837.2 Personnel Training 31937.3 Awareness of Energy Conversion and Management as an Intersectoral Discipline 32037.4 Climate Change 32137.5 Economic Policy Options 32637.6 Policy in Practice 32837.7 Green Economy 33037.8 The Relationship between the Economy and the Environment 33237.8.1 Assessing Pollution’s Environmental Impact 33437.8.2 Ecosystem Recovery and Rehabilitation 33537.8.3 Sustainable Development Ideology 33837.9 Industrial Ecology 33837.9.1 Ecosystem’s Health and Adaptability 34037.10 Does Protecting the Environment Harm the Economy? 34337.10.1 Market and Accounting Mechanism 34437.10.2 UN Environment Program (UNEP) 34537.11 Creating a Green Economy 34637.11.1 Green Project Financing 34737.11.2 Natural Capital Sustainably 34837.11.3 Partnerships 34937.11.4 Educational Sustainability 34937.11.5 Environment Friendly Technologies 350References 351About the Editors 353Index 355

Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. 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.

• Preface xv23 Energy Economics and Environment 1P. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh NikokarAbbreviations 123.1 Introduction 223.1.1 The Concept of Microgrids 323.2 Benefits and Drawbacks of Microgrids 423.3 Causes of Increase in Power Plants 623.4 Demand Side Management in Microgrids 623.5 Centralized Control of Smart Grid 823.6 Decentralized Smart Grid Control 923.7 DER Resource Control Strategies in the Smart Grid 1023.8 DER Participation Strategy in Smart Grid 1123.9 Topics Raised in the Smart Grid 1223.10 Smart Grid Protection 1223.11 Detection of Smart Grid Islands 1223.12 Smart Grid Optimization 1323.13 Power Quality 1323.14 Frequency and Voltage Control 1323.15 Balance between Production and Power Consumption 1423.16 Ability to Easily Connect Distributed Generation Sources 1423.17 Smart Network Security 1423.18 Resynchronization after Network Connection 1523.19 Smart Grid Control Glasses 1523.20 Economic Dimensions 1523.21 Losses 1723.22 Non-Technical Network Losses 1823.23 Power System Loss Analysis 1923.24 The Impact of the Electricity Market on the Performance of Distribution Companies 1923.25 Power Quality in the Restructured Electricity Market 2023.26 Conclusion 20References 2124 Stringent Energy Management Strategy during Covid-19 Pandemic 25Nagajayanthi B.24.1 Introduction 2624.2 Energy Management 2624.3 Smart Grid Design 2724.3.1 Ground Station 2724.3.2 Gateway 2724.3.3 Cloud 2924.4 Smart Grid Design and Testing 3124.5 Implementation of Smart Grid 3524.6 Energy Management to Check Overload Conditions 3724.6.1 With Varying Input Voltage and Without Load 3824.6.2 With Increased Input Voltage but Without Load 4024.6.3 With Optimum Input Voltage and Load 4124.7 Features of Smart Grid System 4624.8 Conclusion and Future Work 47References 4725 Energy Management Strategy for Control and Planning 49Anmol D. Ganer25.1 Energy Management and Audit 5025.1.1 Steps for Energy Audit Management 5125.1.2 How An Energy Audit can be An Effective Energy Management 5125.1.3 Power Conservation through Energy Audit 5125.1.4 Study of Energy Management and Audit 5225.2 The Different Steps of an Energy Management Approach 5225.2.1 State-Wise Generation Capacity till 2019 5325.2.2 The Effective Plan should Incorporate Four Basic Steps 5425.3 Preliminary Technical and Economic 5525.3.1 Assessment of Synthetic Gas to Fuel and Chemical with Emphasis on the Potential for Biomass Derived Syngas 5525.3.2 Natural Gas Storage/Co-Fired Retrofit System 5625.4 Evaluation of Energy-Saving Investments 5625.4.1 Power Survey – Energy Inspection 5725.5 Off-Line and On-Line Procedures 5825.5.1 Concept 5825.6 Personnel Training 5925.6.1 Training Method for Electricity Work Safety 6025.7 A Successful Energy Management Program 6025.7.1 Introduction 6025.7.2 Power Administration Project 6025.7.3 Corporate Structure 6125.7.4 Energy Management Managers 6125.8 Centralize Control of Process and Facility Plants 6225.8.1 Centralized and Decentralized Waste Water Management 6225.8.2 Central Jurisdiction System 6325.8.3 Centralized Process Control System 6325.9 Energy Security 6325.9.1 Energy Security Concept 6325.9.2 Smart Grid Security 6525.10 Evaluate Energy Performances 6525.10.1 Concept 6525.10.2 Building Energy Performance 6525.10.3 Illumination and Energy Performance 6525.10.4 Energy Performance of Water Chillers 6625.11 Energy Action Planning 6625.12 Energy Economics 6725.13 Case Study 67References 6826 Day-Ahead Solar Power Forecasting Using Statistical and Machine Learning Methods 71Aadyasha Patel and O.V. Gnana SwathikaAbbreviations 7226.1 Introduction 7426.2 Durations of Forecasting 7626.3 Forecasting Techniques 7726.4 Statistical Methods 8326.4.1 Grey-Box Model (GB) 8326.4.2 Grey Theory (GT) 8326.4.3 Markov Chain Model (MM) 8326.4.4 Bayesian Optimization 8326.4.5 Linear Pool Ensemble (LPE) 8426.4.6 Variational Mode Decomposition (VMD) 8426.4.7 Autoregressive Integrated Moving Average (ARIMA) 8426.4.8 Quantile Regression Averaging (QRA) 8426.4.9 Logistic Model Trees 8426.4.10 k-Nearest Neighbours (kNN) 8526.5 Machine Learning Techniques 8526.5.1 Machine Learning (ML) 8526.5.2 Automatic Machine Learning (AML) 8526.5.3 Extreme Learning Machine (ELM) 8526.5.4 Quantile Random Forest (QRF) 8626.5.5 Support Vector Regression (SVR) 8626.5.6 Least-Square Support Vector Machine (LSSVM) 8626.5.7 Principal Component Analysis (PCA) 8626.5.8 Hierarchical Similarity-Based Forecasting Model (hSBFM) 8726.5.9 Local Sensitive Hashing Algorithm (LSH) 8726.6 Deep Learning (DL) 8726.6.1 Artificial Neural Network (ANN) 8726.6.2 Feed Forward Neural Network (FFNN) 8726.6.3 Convolutional Neural Network (CNN) 8826.6.4 Elman-Based Neural Network (ENN) 8826.6.5 Deep Belief Network (DBN) 8826.6.6 Long Short-Term Memory (LSTM) 8826.6.7 Autoencoder Long Short-Term Memory (AE-LSTM) 8926.6.8 Self-Organizing Maps (SOM) 8926.7 Evaluation Index and Metrics 8926.8 Conclusions 96References 9727 A Review on Optimum Location and Sizing of DGs in Radial Distribution System 103P. Tejaswi and O.V. Gnana SwathikaAbbreviations 10327.1 Introduction 10427.1.1 DG Planning Based on Multi-Objective Optimization Techniques 10827.1.2 Optimal Placement and Sizing of DG Based on Multi-Objective Optimization Techniques 11027.2 Proposed Location and Sizing of DGs in RDS Using Analytical and PSO Methods 11427.2.1 Methodology 11427.2.1.1 Distribution Load Flow Solution 11427.2.1.2 Multiple DG Allocation and DG Size 11627.2.1.3 PSO Algorithm 11827.2.2 Multi-Objective Function 11927.3 Result 12027.4 Conclusion 12327.5 Appendix: List of Symbols 124References 12428 High Step Up Non-Isolated DC-DC Converter Using Active-Passive Inductor Cells 133Kanimozhi, G., Amritha, G. and O.V. Gnana Swathika28.1 Introduction 13328.2 Proposed Converter 13528.2.1 Features of the Suggested Converter 13628.3 Modes of Operation 13728.4 Design Considerations 14028.5 Simulation 14228.5.1 Simulation for n= 1 14328.5.2 Simulation Results for n= 2 14428.6 Hardware Results 14428.7 Conclusion 148References 14929 A Non-Isolated Step-Up Quasi Z-Source Converter Using Coupled Inductor 151Shashank, P.C. and Kanimozhi, G.29.1 Introduction 15129.2 Improved Quasi Z Source Converter with Coupled Inductor 15429.3 Modes of Operation 15429.4 Simulation Results 15829.5 Comparison 16329.6 Conclusion 165References 16530 Datalogger Aided Stand-Alone PV System for Rural Electrification 167Aashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana SwathikaAbbreviations and Nomenclature 16830.1 Introduction 16930.1.1 Motivation 16930.1.2 Objectives 17030.2 Work Description 17030.2.1 Overview of the Work 17030.2.2 Literature Review 17030.2.3 Methodologies 17230.2.4 Optimization Techniques 17430.2.5 IoT and Smart Technologies 17530.2.6 Conclusion 17730.3 Design and Realisation of dl 17730.3.1 dl Description 17730.3.2 Solar Panel 17730.3.3 Arduino Uno and IDE 17930.3.4 Voltage Sensor 18030.3.5 Current Sensor 18230.3.6 PLX-DAQ Data Acquisition Tool 18430.3.7 Software Specifications 18630.3.8 Methodology 18630.3.8.1 Data Logging into Excel Macro Spreadsheet 18730.3.8.2 Prediction Using Mathematical Model 18830.4 Results 19030.4.1 Prediction Results 19030.4.2 Performance Metrics 19230.4.2.1 Mape 19230.5 Conclusion 19630.5.1 Cost Calculation 19630.5.2 Scope of Work 19630.5.3 Summary 196References 19731 Working and Analysis of an Electromagnet-Based DC V-Gate Magnet Motor for Electrical Applications 201G. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja31.1 Conceptual Introduction 20231.2 Existing Technologies to Review 20331.3 Proposed Design 20431.4 Block Schematic 20531.5 Motor Assembly and Control Structure 20631.6 Control Operation of the V-Gate Magnet Motor 20731.7 Results and Analysis 20831.8 Conclusion and Further Scope of Research 213References 21432 Design and Realization of Smart and Energy-Efficient Doorbell 217Shubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.32.1 Introduction 21832.2 Methodology 21832.3 Design and Specification 21932.3.1 Software-Based Approach 21932.3.1.1 Component Used 22032.3.1.2 Circuit Diagram 22132.3.2 Hardware-Based Approach 22132.3.2.1 Components Used 22232.3.2.2 Circuit Diagram 22332.4 Result and Discussion 22432.5 Conclusion 228References 22933 Optimal Solar Charging Enabled Autonomous Cleaning Robot 231Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika33.1 Introduction 23133.2 Methodology 23333.2.1 Design Specification 23333.2.2 Trash Detection 23633.2.3 Movement Algorithm 23833.2.4 Solar Charging 24133.2.5 Remote Monitoring 24233.3 Results 24333.3.1 Trash Detection Results 24333.3.2 Solar Charging Results 24533.3.3 Remote Monitoring Dashboard 24533.4 Conclusion 246References 24634 Real-Time Health Monitoring System of a Distribution Transformer 249Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika34.1 Introduction 24934.2 Flow Diagram 25034.3 Operating Principle 25034.4 Observation and Result 25234.5 IFTTT Email Notification (in case of a fault) 25334.6 Conclusion 253References 25335 Analysis of Wide-Angle Polarization-Insensitive Metamaterial Absorber Using Equivalent Circuit Modeling for Energy Harvesting Application 255Kanwar Preet Kaur and Trushit Upadhyaya35.1 Introduction 25535.2 Absorber Theory and Proposed Unit Cell Design 25735.3 Equivalent Circuit Model 25835.4 Simulation Results 26035.4.1 Retrieval of the Effective MMA Parameters 26135.4.2 Absorption Mechanism 26235.4.3 Polarization Angle and Oblique Angle Variations 26235.4.4 Resistive Load Variations 26235.5 Experimental Results 26835.6 Conclusion 270References 27136 World Energy Demand 275Satish R. Billewar, Gaurav Londhe and Pradip Suresh Mane36.1 Energy End Users 27636.2 Rural Electrification 28136.3 Residential and Non-Residential Buildings 28236.3.1 Urban and Semi-Urban Zones Power Requirement 28336.3.2 Rural Residential Requirements 28436.3.3 Non Residential Buildings 28436.4 Industry 28636.4.1 Industrialization, the Environment, and Pollution 28736.4.2 Green Industry Initiative 29236.5 Transport 29436.5.1 The United Nations Environment Programme (unep) 29436.5.2 The Initiatives of Countries 29536.5.3 Sustainable Development Goals (SDGs) 29636.5.4 Economic Sector Initiatives 29936.5.5 Social Sector Initiatives 30036.5.6 Environmental Sector Initiatives 30036.5.7 The ASI Approach 30136.6 Agriculture 30236.6.1 Soil Fertility and Irrigation 30536.6.2 Pesticides and Biomass Pollution Control 30536.6.3 Agroforestry 30736.6.4 Biotechnologies 30836.7 Performance Mapping in Conjunction with Technological Evolution 310References 31537 Education in Energy Conversion and Management 317Satish R. Billewar, Karuna Jadhav and Gaurav Londhe37.1 Role of University 31837.2 Personnel Training 31937.3 Awareness of Energy Conversion and Management as an Intersectoral Discipline 32037.4 Climate Change 32137.5 Economic Policy Options 32637.6 Policy in Practice 32837.7 Green Economy 33037.8 The Relationship between the Economy and the Environment 33237.8.1 Assessing Pollution’s Environmental Impact 33437.8.2 Ecosystem Recovery and Rehabilitation 33537.8.3 Sustainable Development Ideology 33837.9 Industrial Ecology 33837.9.1 Ecosystem’s Health and Adaptability 34037.10 Does Protecting the Environment Harm the Economy? 34337.10.1 Market and Accounting Mechanism 34437.10.2 UN Environment Program (UNEP) 34537.11 Creating a Green Economy 34637.11.1 Green Project Financing 34737.11.2 Natural Capital Sustainably 34837.11.3 Partnerships 34937.11.4 Educational Sustainability 34937.11.5 Environment Friendly Technologies 350References 351About the Editors 353Index 355