Freshly Printed - allow 7 days lead
Couldn't load pickup availability
Integrated Green Energy Solutions, Volume 2
Milind Shrinivas Dangate (Edited by), Dangate (Author), W. S. Sampath (Edited by), O. V. Gnana Swathika (Edited by), Sanjeevikumar Padmanaban (Edited by)
9781394193660, Wiley
Hardback, published 7 June 2023
384 pages
22.9 x 15.2 x 2.4 cm, 0.776 kg
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.
Preface xv 23 Energy Economics and Environment 1 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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
P. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh Nikokar
Nagajayanthi B.
Anmol D. Ganer
Aadyasha Patel and O.V. Gnana Swathika
P. Tejaswi and O.V. Gnana Swathika
Kanimozhi, G., Amritha, G. and O.V. Gnana Swathika
Shashank, P.C. and Kanimozhi, G.
Aashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana Swathika
G. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja
Shubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.
Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
Aastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
Kanwar Preet Kaur and Trushit Upadhyaya
Satish R. Billewar, Gaurav Londhe and Pradip Suresh Mane
Satish R. Billewar, Karuna Jadhav and Gaurav Londhe
Subject Areas: Electronics & communications engineering [TJ]
