Smart Grids and Internet of Things An Energy Perspective

Smart grids and the Internet of Things (IoT) are rapidly changing and complicated subjects that are constantly changing and developing. This new volume addresses the current state-of-the-art concepts and technologies associated with the technologies and covers new ideas and emerging novel technologies and processes.

Internet of Things (IoT) is a self-organized network that consists of sensors, software, and devices. The data is exchanged among them with the help of the internet. Smart Grids (SG) is a collection of devices deployed in larger areas to perform continuous monitoring and analysis in that region. It is responsible for balancing the flow of energy between the servers and consumers. SG also takes care of the transmission and distribution power to the components involved. The tracking of the devices present in SG is achieved by the IoT framework. Thus, assimilating IoT and SG will lead to developing solutions for many real-time problems.

This exciting new volume covers all of these technologies, including the basic concepts and the problems and solutions involved with the practical applications in the real world. Whether for the veteran engineer or scientist, the student, or a manager or other technician working in the field, this volume is a must-have for any library.

Smart Grids and Internet of Things:

• Presents Internet of Things (IoT) and smart grid (SG)-integrated frameworks along with their components and technologies
• Covers the challenges in energy harvesting and sustainable solutions for IoTSGs and their solutions for practical applications
• Describes and demystifies the privacy and security issues while processing data in IoTSG
• Includes case studies relating to IoTSG with cloud and fog computing machine learning and blockchain

Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark and works with CTIF Global Capsule (CGC), Department of Business Development and Technology, Aarhus University, Denmark. 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. 

Jens Bo Holm-Nielsen currently works at the Department of Energy Technology, Aalborg University and is head of the Esbjerg Energy Section. He helped establish the Center for Bioenergy and Green Engineering in 2009 and served as the head of the research group. He has served as technical advisor for many companies in this industry, and he has executed many large-scale European Union and United Nation projects.  He has authored more than 300 scientific papers and has participated in over 500 various international conferences.

Rajesh Kumar Dhanaraj is a professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India.  He received his PhD in computer science from Anna University, Chennai, India. He has contributed to over 25 books and has 17 patents to his credit.  He has also authored over 40 articles and papers in various refereed journals and international conferences.

Malathy Sathyamoorthy is an assistant professor in the Department of Computer Science and Engineering at Kongu engineering college. She is pursuing her PhD in wireless sensor networks and has authored or co-authored over 40 papers in refereed journals and book chapters.

Balamurugan Balusamy is a professor in the School of Computing Science and Engineering, Galgotias University, Greater Noida, India.  He received his PhD in computer science and engineering from VIT University, Vellore, India and has published over 70 articles in scientific journals.

Preface xvii

1 Introduction to the Internet of Things: Opportunities, Perspectives and Challenges 1
F. Leo John, D. Lakshmi and Manideep Kuncharam

1.1 Introduction 2

1.1.1 The IOT Data Sources 4

1.1.2 IOT Revolution 6

1.2 IOT Platform 8

1.3 IOT Layers and its Protocols 10

1.4 Architecture and Future Problems for IOT Protection 27

1.5 Conclusion 32

References 32

2 Role of Battery Management System in IoT Devices 35
R. Deepa, K. Mohanraj, N. Balaji and P. Ramesh Kumar

2.1 Introduction 36

2.1.1 Types of Lithium Batteries 36

2.1.1.1 Lithium Battery (LR) 37

2.1.1.2 Button Type Lithium Battery (BLB) 37

2.1.1.3 Coin Type Lithium Battery (CLB) 37

2.1.1.4 Lithium-Ion Battery (LIB) 37

2.1.1.5 Lithium-Ion Polymer Battery (LIP) 37

2.1.1.6 Lithium Cobalt Battery (LCB) 38

2.1.1.7 Lithium Manganese Battery (LMB) 38

2.1.1.8 Lithium Phosphate Battery (LPB) 38

2.1.1.9 Lithium Titanate Battery (LTB) 38

2.1.2 Selection of the Battery 38

2.1.2.1 Nominal Voltage 39

2.1.2.2 Operating Time 39

2.1.2.3 Time for Recharge and Discharge 39

2.1.2.4 Cut Off Voltage 39

2.1.2.5 Physical Dimension 39

2.1.2.6 Environmental Conditions 40

2.1.2.7 Total Cost 40

2.2 Internet of Things 41

2.2.1 IoT – Battery Market 43

2.2.2 IoT - Battery Marketing Strategy 44

2.2.2.1 Based on the Type 44

2.2.2.2 Based on the Rechargeability 45

2.2.2.3 Based on the Region 45

2.2.2.4 Based on the Application 45

2.3 Power of IoT Devices in Battery Management System 45

2.3.1 Power Management 46

2.3.2 Energy Harvesting 47

2.3.3 Piezo-Mechanical Harvesting 48

2.3.4 Batteries Access to IoT Pioneers 49

2.3.5 Factors for Powering IoT Devices 49

2.3.5.1 Temperature 50

2.3.5.2 Environmental Factors 50

2.3.5.3 Power Budget 50

2.3.5.4 Form Factor 51

2.3.5.5 Status of the Battery 51

2.3.5.6 Shipment 52

2.4 Battery Life Estimation of IoT Devices 52

2.4.1 Factors Affecting the Battery Life of IoT Devices 53

2.4.2 Battery Life Calculator 53

2.4.3 Sleep Modes of IoT Processors 55

2.4.3.1 No Sleep 55

2.4.3.2 Modem Sleep 55

2.4.3.3 Light Sleep 55

2.4.3.4 Deep Sleep 56

2.4.4 Core Current Consumption 56

2.4.5 Peripheral Current Consumption 59

2.5 IoT Networking Technologies 59

2.5.1 Selection of an IoT Sensor 60

2.5.2 IoT - Battery Technologies 60

2.5.3 Battery Specifications 61

2.5.4 Battery Shelf Life 62

2.6 Conclusion 62

References 63

3 Smart Grid - Overview, Challenges and Security Issues 67
C. N. Vanitha, Malathy S. and S.A. Krishna

3.1 Introduction to the Chapter 68

3.2 Smart Grid and Its Uses 69

3.3 The Grid as it Stands-What’s at Risk? 72

3.3.1 Reliability 73

3.3.2 Efficiency 73

3.3.3 Security 74

3.3.4 National Economy 74

3.4 Creating the Platform for Smart Grid 75

3.4.1 Consider the ATM 76

3.5 Smart Grid in Power Plants 77

3.5.1 Distributed Power Flow Control 78

3.5.2 Power System Automation 79

3.5.3 IT Companies Disrupting the Energy Market 79

3.6 Google in Smart Grid 80

3.7 Smart Grid in Electric Cars 81

3.7.1 Vehicle-to-Grid 82

3.7.2 Challenges in Smart Grid Electric Cars 83

3.7.3 Toyota and Microsoft in Smart Electric Cars 84

3.8 Revisit the Risk 85

3.8.1 Reliability 85

3.8.2 Efficiency 86

3.8.3 Security 87

3.8.4 National Economy 88

3.9 Summary 88

References 88

4 IoT-Based Energy Management Strategies in Smart Grid 91
Seyed Ehsan Ahmadi and Sina Delpasand

4.1 Introduction 92

4.2 Application of IoT for Energy Management in Smart Grids 93

4.3 Energy Management System 94

4.3.1 Objectives of EMS 94

4.3.2 Control Frameworks of EMS 95

4.3.2.1 Centralized Approach 96

4.3.2.2 Decentralized Approach 97

4.3.2.3 Hierarchical Approach 97

4.4 Types of EMS at Smart Grid 98

4.4.1 Smart Home EMS 99

4.4.2 Smart Building EMS 100

4.5 Participants of EMS 103

4.5.1 Network Operator 104

4.5.2 Data and Communication Technologies 105

4.5.3 Aggregators 107

4.6 DER Scheduling 108

4.7 Important Factors for EMS Establishment 111

4.7.1 Uncertainty Modeling and Management Methods 111

4.7.2 Power Quality Management 112

4.7.3 DSM and DR Programs 114

4.8 Optimization Approaches for EMS 115

4.8.1 Mathematical Approaches 117

4.8.2 Heuristic Approaches 118

4.8.3 Metaheuristic Approaches 119

4.8.4 Other Programming Approaches 119

4.9 Conclusion 121

References 121

5 Integrated Architecture for IoTSG: Internet of Things (IoT) and Smart Grid (SG) 127
Malathy S., K. Sangeetha, C. N. Vanitha and Rajesh Kumar Dhanaraj

5.1 Introduction 128

5.1.1 Designing of IoT Architecture 129

5.1.2 IoT Characteristics 132

5.2 Introduction to Smart Grid 134

5.2.1 Smart Grid Technologies (SGT) 136

5.3 Integrated Architecture of IoT and Smart Grid 138

5.3.1 Safety Concerns 140

5.3.2 Security Issues 142

5.4 Smart Grid Security Services Based on IoT 143

References 154

6 Exploration of Assorted Modernizations in Forecasting Renewable Energy Using Low Power Wireless Technologies for IoTSG 157
Logeswaran K., Suresh P., Ponselvakumar A.P., Savitha S., Sentamilselvan K. and Adhithyaa N.

6.1 Introduction to the Chapter 158

6.1.1 Fossil Fuels and Conventional Grid 158

6.1.2 Renewable Energy and Smart Grid 160

6.2 Intangible Architecture of Smart Grid (SG) 161

6.3 Internet of Things (IoT) 164

6.4 Renewable Energy Source (RES)- Key Technology for SG 167

6.4.1 Renewable Energy: Basic Concepts and Readiness 167

6.4.2 Natural Sources of Renewable Energy 169

6.4.3 Major Issues in Following RES to SG 173

6.4.4 Integration of RES with SG 176

6.4.5 SG Renewable Energy Management Facilitated by IoT 177

6.4.6 Case Studies on Smart Grid: Renewable Energy Perception 180

6.5 Low Power Wireless Technologies for IoTSG 181

6.5.1 Role of IoT in SG 181

6.5.2 Innovations in Low Power Wireless Technologies 182

6.5.3 Wireless Communication Technologies for IoTSG 183

6.5.4 Case Studies on Low Power Wireless Technologies Used in IoTSG 186

6.6 Conclusion 188

References 188

7 Effective Load Balance in IOTSG with Various Machine Learning Techniques 193
Thenmozhi K., Pyingkodi M. and Kanimozhi K.

I. Introduction 194

II. IoT in Big Data 195

III. IoT in Machine Learning 197

IV. Machine Learning Methods in IoT 199

V. IoT with SG 200

VI. Deep Learning with IoT 201

VII. Challenges in IoT for SG 202

VIII. IoT Applications for SG 202

IX. Application of IoT in Various Domain 204

X. Conclusion 205

References 206

8 Fault and Delay Tolerant IoT Smart Grid 207
K. Sangeetha and P. Vishnu Raja

8.1 Introduction 207

8.1.1 The Structures of the Intelligent Network 209

8.1.1.1 Operational Competence 209

8.1.1.2 Energy Efficiency 209

8.1.1.3 Flexibility in Network Topology 210

8.1.1.4 Reliability 210

8.1.2 Need for Smart Grid 210

8.1.3 Motivation for Enabling Delay Tolerant IoT 211

8.1.4 IoT-Enabled Smart Grid 211

8.2 Architecture 212

8.3 Opportunities and Challenges in Delay Tolerant Network for the Internet of Things 215

8.3.1 Design Goals 215

8.4 Energy Efficient IoT Enabled Smart Grid 219

8.5 Security in DTN IoT Smart Grid 220

8.5.1 Safety Problems 220

8.5.2 Safety Works for the Internet of Things-Based Intelligent Network 221

8.5.3 Security Standards for the Smart Grid 222

8.5.3.1 The Design Offered by NIST 222

8.5.3.2 The Design Planned by IEEE 222

8.6 Applications of DTN IoT Smart Grid 224

8.6.1 Household Energy Management in Smart Grids 224

8.6.2 Data Organization System for Rechargeable Vehicles 224

8.6.3 Advanced Metering Infrastructure (AMI) 225

8.6.4 Energy Organization 226

8.6.5 Transmission Tower Protection 226

8.6.6 Online Monitoring of Power Broadcast Lines 227

8.7 Conclusion 227

References 228

9 Significance of Block Chain in IoTSG - A Prominent and Reliable Solution 235
S. Vinothkumar, S. Varadhaganapathy, R. Shanthakumari and M. Ramalingam

9.1 Introduction 236

9.2 Trustful Difficulties with Monetary Communications for IoT Forum 239

9.3 Privacy in Blockchain Related Work 242

9.4 Initial Preparations 244

9.4.1 Blockchain Overview 244

9.4.2 k-Anonymity 246

9.4.2.1 Degree of Anonymity 246

9.4.2.2 Data Forfeiture 247

9.5 In the IoT Power and Service Markets, Reliable Transactions and Billing 248

9.5.1 Connector or Bridge 250

9.5.2 Group of Credit-Sharing 251

9.5.3 Local Block 251

9.6 Potential Applications and Use Cases 253

9.6.1 Utilities and Energy 253

9.6.2 Charging of Electric Vehicles 253

9.6.3 Credit Transfer 254

9.7 Proposed Work Execution 254

9.7.1 Creating the Group of Energy Sharing 255

9.7.2 Handling of Transaction 255

9.8 Investigation of Secrecy and Trustworthy 259

9.8.1 Trustworthy 259

9.8.2 Privacy-Protection 260

9.8.2.1 Degree of Confidentiality 261

9.8.2.2 Data Forfeiture 263

9.8.3 Evaluation of Results 265

9.9 Conclusion 267

References 267

10 IoTSG in Maintenance Management 273
T.C. Kalaiselvi and C.N. Vanitha

10.1 Introduction to the Chapter 274

10.2 IoT in Smart Grid 276

10.2.1 Uses and Facilities in SG 278

10.2.2 Architectures in SG 280

10.3 IoT in the Generation Level, Transmission Level, Distribution Level 288

10.4 Challenges and Future Research Directions in SG 295

10.5 Components for Predictive Management 296

10.6 Data Management and Infrastructure of IoT for Predictive Management 298

10.6.1 PHM Algorithms for Predictive Management 303

10.6.2 Decision Making with Predictive Management 305

10.7 Research Challenges in the Maintenance of Internet of Things 310

10.8 Summary 315

References 315

11 Intelligent Home Appliance Energy Monitoring with IoT 319
S. Tamilselvan, D. Deepa, C. Poongodi, P. Thangavel and Sarumathi Murali

11.1 Introduction 320

11.2 Survey on Energy Monitoring 320

11.3 Internet of Things System Architecture 322

11.4 Proposed Energy Monitoring System with IoT 323

11.5 Energy Management Structure (Proposed) 324

11.6 Implementation of the System 325

11.6.1 Implementation of IoT Board 325

11.6.2 Software Implementation 325

11.7 Smart Home Automation Forecasts 326

11.7.1 Energy Measurement 326

11.7.2 Periodically Updating the Status in the Cloud 327

11.7.3 Irregularity Detection 328

11.7.4 Finding the Problems with the Device 328

11.7.5 Indicating the House Owner About the Issues 329

11.7.6 Suggestions for Remedial Actions 329

11.8 Energy Reduction Based on IoT 330

11.8.1 House Energy Consumption (HEC) - Cost Saving 330

11.9 Performance Evaluation 330

11.9.1 Data Analytics and Visualization 330

11.10 Benefits for Different User Categories 332

11.11 Results and Discussion with Benefits of User Categories 332

11.12 Summary 334

References 334

12 Applications of IoTSG in Smart Industrial Monitoring Environments 339
Mohanasundaram T., Vetrivel S.C., and Krishnamoorthy V.

12.1 Introduction 340

12.2 Energy Management 342

12.3 Role of IoT and Smart Grid in the Banking Industry 345

12.3.1 Application of IoT in the Banking Sector 346

12.3.1.1 Customer Relationship Management (crm) 347

12.3.1.2 Loan Sanctions 348

12.3.1.3 Customer Service 348

12.3.1.4 Leasing Finance Automation 348

12.3.1.5 Capacity Management 348

12.3.2 Application of Smart Grid in the Banking Sector 349

12.4 Role of IoT and Smart Grid in the Automobile Industry 349

12.4.1 Application of IoT in the Automobile Industry 350

12.4.1.1 What Exactly is the Internet of Things (IoT) Mean to the Automobile Sector? 350

12.4.1.2 Transportation and Logistics 351

12.4.1.3 Connected Cars 351

12.4.1.4 Fleet Management 352

12.4.2 Application of Smart Grid (SG) in the Automobile Industry 354

12.4.2.1 Smart Grid Can Change the Face of the Automobile Industry 355

12.4.2.2 Smart Grid and Energy Efficient Mobility System 357

12.5 Role of IoT and SG in Healthcare Industry 357

12.5.1 Applications of IoT in Healthcare Sector 358

12.5.2 Application of Smart Grid (SG) in Health Care Sector 360

12.6 IoT and Smart Grid in Energy Management - A Way Forward 360

12.7 Conclusion 362

References 363

13 Solar Energy Forecasting for Devices in IoT Smart Grid 365
K. Tamil Selvi, S. Mohana Saranya and R. Thamilselvan

13.1 Introduction 366

13.2 Role of IoT in Smart Grid 368

13.3 Clear Sky Models 370

13.3.1 REST2 Model 370

13.3.2 Kasten Model 370

13.3.3 Polynomial Fit 371

13.4 Persistence Forecasts 372

13.5 Regressive Methods 373

13.5.1 Auto-Regressive Model 373

13.5.2 Moving Average Model 373

13.5.3 Mixed Auto Regressive Moving Average Model 373

13.5.4 Mixed Auto Regressive Moving Average Model with Exogeneous Variables 374

13.6 Non-Linear Stationary Models 374

13.7 Linear Non-Stationary Models 376

13.7.1 Auto Regressive Integrated Moving Average Models 376

13.7.2 Auto-Regressive Integrated Moving Average Model with Exogenous Variables 376

13.8 Artificial Intelligence Techniques 377

13.8.1 Artificial Neural Network 377

13.8.2 Multi-Layer Perceptron 377

13.8.3 Deep Learning Model 380

13.8.3.1 Stacked Auto-Encoder 381

13.8.3.2 Deep Belief Network 382

13.8.3.3 Deep Recurrent Neural Network 383

13.8.3.4 Deep Convolutional Neural Network 384

13.8.3.5 Stacked Extreme Learning Machine 386

13.8.3.6 Generative Adversarial Network 386

13.8.3.7 Comparison of Deep Learning Models for Solar Energy Forecast 387

13.9 Remote Sensing Model 389

13.10 Hybrid Models 389

13.11 Performance Metrics for Forecasting Techniques 390

13.12 Conclusion 391

References 392

14 Utilization of Wireless Technologies in IoTSG for Energy Monitoring in Smart Devices 395
S. Suresh Kumar, A. Prakash, O. Vignesh and M. Yogesh Iggalore

14.1 Introduction to Internet of Things 396

14.2 IoT Working Principle 397

14.3 Benefits of IoT 398

14.4 IoT Applications 399

14.5 Introduction to Smart Home 399

14.5.1 Benefits of Smart Homes 400

14.6 Problem Statement 401

14.6.1 Methodology 401

14.7 Introduction to Wireless Communication 402

14.7.1 Merits of Wireless 402

14.8 How Modbus Communication Works 403

14.8.1 Rules for Modbus Addressing 404

14.8.2 Modbus Framework Description 404

14.8.2.1 Function Code 404

14.8.2.2 Cyclic Redundancy Check 405

14.8.2.3 Data Storage in Modbus 405

14.9 MQTT Protocol 406

14.9.1 Pub/Sub Architecture 406

14.9.2 MQTT Client Broker Communication 407

14.9.3 MQTT Standard Header Packet 407

14.9.3.1 Fixed Header 408

14.10 System Architecture 408

14.11 IoT Based Electronic Energy Meter-eNtroL 410

14.11.1 Components Used in eNtroL 411

14.11.2 PZEM-004t Energy Meter 411

14.11.3 Wi-Fi Module 412

14.11.4 Switching Device 413

14.11.5 230V AC to 5V Dc Converter 414

14.11.6 LM1117 IC- 5V to 3.3V Converter 414

14.12 AC Control System for Home Appliances – Switch2Smart 415

14.12.1 Opto-Coupler- H11AA1 IC 415

14.12.2 TRIAC Driven Opto Isolator- MOC3021M IC 416

14.12.3 Triac, Bt136-600 Ic 416

14.13 Scheduling Home Appliance Using Timer – Switch Binary 417

14.14 Hardware Design 418

14.14.1 Kaicad Overview 418

14.14.2 PCB Designing Using Kaicad 418

14.14.2.1 Designing of eNtroL Board Using Kaicad 418

14.14.2.2 Designing of Switch2smart Board Using Kaicad 420

14.14.2.3 Designing of Switch Binary Board Using Kaicad 421

14.15 Implementation of the Proposed System 422

14.16 Testing and Results 424

14.16.1 Testing of eNtrol 425

14.16.2 Testing of Switch2Smart 427

14.16.3 Testing of SwitchBinary 428

14.17 Conclusion 429

References 429

15 Smart Grid IoT: An Intelligent Energy Management in Emerging Smart Cities 431
R. S. Shudapreyaa, G. K. Kamalam, P. Suresh and K. Sentamilselvan

15.1 Overview of Smart Grid and IoT 432

15.1.1 Smart Grid 432

15.1.2 Smart Grid Data Properties 434

15.1.3 Operations on Smart Grid Data 435

15.2 IoT Application in Smart Grid Technologies 436

15.2.1 Power Transmission Line - Online Monitoring 436

15.2.2 Smart Patrol 437

15.2.3 Smart Home Service 437

15.2.4 Information System for Electric Vehicle 438

15.3 Technical Challenges of Smart Grid 438

15.3.1 Inadequacies in Grid Infrastructure 438

15.3.2 Cyber Security 439

15.3.3 Storage Concerns 439

15.3.4 Data Management 440

15.3.5 Communication Issues 440

15.3.6 Stability Concerns 440

15.3.7 Energy Management and Electric Vehicle 440

15.4 Energy Efficient Solutions for Smart Cities 441

15.4.1 Lightweight Protocols 441

15.4.2 Scheduling Optimization 441

15.4.3 Energy Consumption 441

15.4.4 Cloud Based Approach 441

15.4.5 Low Power Transceivers 442

15.4.6 Cognitive Management Framework 442

15.5 Energy Conservation Based Algorithms 442

15.5.1 Genetic Algorithm (GA) 442

15.5.2 BFO Algorithm 444

15.5.3 BPSO Algorithm 445

15.5.4 WDO Algorithm 447

15.5.5 GWDO Algorithm 447

15.5.6 WBFA Algorithm 450

15.6 Conclusion 451

References 451

Index 455

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