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Smart Grids and Internet of Things

Edited by Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Rajesh Kumar Dhanaraj, Malathy Sathyamoorthy, and Balamurugan Balusamy
Copyright: 2023   |   Status: Published
ISBN: 9781119812449  |  Hardcover  |  
460 pages
Price: $225 USD
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One Line Description
Written and edited by a team of international professionals, this groundbreaking new volume covers the latest technologies in automation, tracking, energy distribution and consumption of Internet of Things (IoT) devices with smart grids.

Audience
Researchers in the field of IoT and smart grids, electrical engineers working on energy distribution and management, researchers working on wireless technologies in data computation and block chain technologies and students in computer science and information technology

Description
Internet of Things (IoT) is a self-organized network which consists of sensors, softwarec 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 transmission and distributing 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 leads to developing solutions for many real-time problems. The wireless communication protocol helps data transmission between the devices involved in IoTSG, and cloud and fog computing helps to process the edge servers with low latency and avoid congestion between the devices which are geographically dispersed. The voluminous data present in the edge servers needs an efficient big data analytics procedure, in order to avoid computation overhead, which in turn helps to save the energy of the devices deployed. In addition to energy harvesting, intelligence of the devices could be improved by incorporating Machine learning (ML) techniques. This also helps IoTSGs to automate the things in a sensible way for real time applications.

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.

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Author / Editor Details
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.

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Table of Contents
Preface
1. Introduction to the Internet of Things: Opportunities, Perspectives and Challenges
F. Leo John, D. Lakshmi and Manideep Kuncharam
1.1 Introduction
1.1.1 The IOT Data Sources
1.1.2 IOT Revolution
1.2 IOT Platform
1.3 IOT Layers and its Protocols
1.4 Architecture and Future Problems for IOT Protection
1.5 Conclusion
References
2. Role of Battery Management System in IoT Devices
R. Deepa, K. Mohanraj, N. Balaji and P. Ramesh Kumar
2.1 Introduction
2.1.1 Types of Lithium Batteries
2.1.1.1 Lithium Battery (LR)
2.1.1.2 Button Type Lithium Battery (BLB)
2.1.1.3 Coin Type Lithium Battery (CLB)
2.1.1.4 Lithium-Ion Battery (LIB)
2.1.1.5 Lithium-Ion Polymer Battery (LIP)
2.1.1.6 Lithium Cobalt Battery (LCB)
2.1.1.7 Lithium Manganese Battery (LMB)
2.1.1.8 Lithium Phosphate Battery (LPB)
2.1.1.9 Lithium Titanate Battery (LTB)
2.1.2 Selection of the Battery
2.1.2.1 Nominal Voltage
2.1.2.2 Operating Time
2.1.2.3 Time for Recharge and Discharge
2.1.2.4 Cut Off Voltage
2.1.2.5 Physical Dimension
2.1.2.6 Environmental Conditions
2.1.2.7 Total Cost
2.2 Internet of Things
2.2.1 IoT – Battery Market
2.2.2 IoT - Battery Marketing Strategy
2.2.2.1 Based on the Type
2.2.2.2 Based on the Rechargeability
2.2.2.3 Based on the Region
2.2.2.4 Based on the Application
2.3 Power of IoT Devices in Battery Management System
2.3.1 Power Management
2.3.2 Energy Harvesting
2.3.3 Piezo-Mechanical Harvesting
2.3.4 Batteries Access to IoT Pioneers
2.3.5 Factors for Powering IoT Devices
2.3.5.1 Temperature
2.3.5.2 Environmental Factors
2.3.5.3 Power Budget
2.3.5.4 Form Factor
2.3.5.5 Status of the Battery
2.3.5.6 Shipment
2.4 Battery Life Estimation of IoT Devices
2.4.1 Factors Affecting the Battery Life of IoT Devices
2.4.2 Battery Life Calculator
2.4.3 Sleep Modes of IoT Processors
2.4.3.1 No Sleep
2.4.3.2 Modem Sleep
2.4.3.3 Light Sleep
2.4.3.4 Deep Sleep
2.4.4 Core Current Consumption
2.4.5 Peripheral Current Consumption
2.5 IoT Networking Technologies
2.5.1 Selection of an IoT Sensor
2.5.2 IoT - Battery Technologies
2.5.3 Battery Specifications
2.5.4 Battery Shelf Life
2.6 Conclusion
References
3. Smart Grid - Overview, Challenges and Security Issues
C. N. Vanitha, Malathy S. and S.A. Krishna
3.1 Introduction to the Chapter
3.2 Smart Grid and Its Uses
3.3 The Grid as it Stands-What’s at Risk?
3.3.1 Reliability
3.3.2 Efficiency
3.3.3 Security
3.3.4 National Economy
3.4 Creating the Platform for Smart Grid
3.4.1 Consider the ATM
3.5 Smart Grid in Power Plants
3.5.1 Distributed Power Flow Control
3.5.2 Power System Automation
3.5.3 IT Companies Disrupting the Energy Market
3.6 Google in Smart Grid
3.7 Smart Grid in Electric Cars
3.7.1 Vehicle-to-Grid
3.7.2 Challenges in Smart Grid Electric Cars
3.7.3 Toyota and Microsoft in Smart Electric Cars
3.8 Revisit the Risk
3.8.1 Reliability
3.8.2 Efficiency
3.8.3 Security
3.8.4 National Economy
3.9 Summary
References
4. IoT-Based Energy Management Strategies in Smart Grid
Seyed Ehsan Ahmadi and Sina Delpasand
4.1 Introduction
4.2 Application of IoT for Energy Management in Smart Grids
4.3 Energy Management System
4.3.1 Objectives of EMS
4.3.2 Control Frameworks of EMS
4.3.2.1 Centralized Approach
4.3.2.2 Decentralized Approach
4.3.2.3 Hierarchical Approach
4.4 Types of EMS at Smart Grid
4.4.1 Smart Home EMS
4.4.2 Smart Building EMS
4.5 Participants of EMS
4.5.1 Network Operator
4.5.2 Data and Communication Technologies
4.5.3 Aggregators
4.6 DER Scheduling
4.7 Important Factors for EMS Establishment
4.7.1 Uncertainty Modeling and Management Methods
4.7.2 Power Quality Management
4.7.3 DSM and DR Programs
4.8 Optimization Approaches for EMS
4.8.1 Mathematical Approaches
4.8.2 Heuristic Approaches
4.8.3 Metaheuristic Approaches
4.8.4 Other Programming Approaches
4.9 Conclusion
References
5. Integrated Architecture for IoTSG: Internet of Things (IoT) and Smart Grid (SG)
Malathy S., K. Sangeetha, C. N. Vanitha and Rajesh Kumar Dhanaraj
5.1 Introduction
5.1.1 Designing of IoT Architecture
5.1.2 IoT Characteristics
5.2 Introduction to Smart Grid
5.2.1 Smart Grid Technologies (SGT)
5.3 Integrated Architecture of IoT and Smart Grid
5.3.1 Safety Concerns
5.3.2 Security Issues
5.4 Smart Grid Security Services Based on IoT
References
6. Exploration of Assorted Modernizations in Forecasting Renewable Energy Using Low Power Wireless Technologies for IoTSG
Logeswaran K., Suresh P., Ponselvakumar A.P., Savitha S., Sentamilselvan K. and Adhithyaa N.
6.1 Introduction to the Chapter
6.1.1 Fossil Fuels and Conventional Grid
6.1.2 Renewable Energy and Smart Grid
6.2 Intangible Architecture of Smart Grid (SG)
6.3 Internet of Things (IoT)
6.4 Renewable Energy Source (RES)- Key Technology for SG
6.4.1 Renewable Energy: Basic Concepts and Readiness
6.4.2 Natural Sources of Renewable Energy
6.4.3 Major Issues in Following RES to SG
6.4.4 Integration of RES with SG
6.4.5 SG Renewable Energy Management Facilitated by IoT
6.4.6 Case Studies on Smart Grid: Renewable Energy Perception
6.5 Low Power Wireless Technologies for IoTSG
6.5.1 Role of IoT in SG
6.5.2 Innovations in Low Power Wireless Technologies
6.5.3 Wireless Communication Technologies for IoTSG
6.5.4 Case Studies on Low Power Wireless Technologies Used in IoTSG
6.6 Conclusion
References
7. Effective Load Balance in IOTSG with Various Machine Learning Techniques
Thenmozhi K., Pyingkodi M. and Kanimozhi K.
I. Introduction
II. IoT in Big Data
III. IoT in Machine Learning
IV. Machine Learning Methods in IoT
V. IoT with SG
VI. Deep Learning with IoT
VII. Challenges in IoT for SG
VIII. IoT Applications for SG
IX. Application of IoT in Various Domain
X. Conclusion
References
8. Fault and Delay Tolerant IoT Smart Grid
K. Sangeetha and P. Vishnu Raja
8.1 Introduction
8.1.1 The Structures of the Intelligent Network
8.1.1.1 Operational Competence
8.1.1.2 Energy Efficiency
8.1.1.3 Flexibility in Network Topology
8.1.1.4 Reliability
8.1.2 Need for Smart Grid
8.1.3 Motivation for Enabling Delay Tolerant IoT
8.1.4 IoT-Enabled Smart Grid
8.2 Architecture
8.3 Opportunities and Challenges in Delay Tolerant Network for the Internet of Things
8.3.1 Design Goals
8.4 Energy Efficient IoT Enabled Smart Grid
8.5 Security in DTN IoT Smart Grid
8.5.1 Safety Problems
8.5.2 Safety Works for the Internet of Things-Based Intelligent Network
8.5.3 Security Standards for the Smart Grid
8.5.3.1 The Design Offered by NIST
8.5.3.2 The Design Planned by IEEE
8.6 Applications of DTN IoT Smart Grid
8.6.1 Household Energy Management in Smart Grids
8.6.2 Data Organization System for Rechargeable Vehicles
8.6.3 Advanced Metering Infrastructure (AMI)
8.6.4 Energy Organization
8.6.5 Transmission Tower Protection
8.6.6 Online Monitoring of Power Broadcast Lines
8.7 Conclusion
References
9. Significance of Block Chain in IoTSG - A Prominent and Reliable Solution
S. Vinothkumar, S. Varadhaganapathy, R. Shanthakumari and M. Ramalingam
9.1 Introduction
9.2 Trustful Difficulties with Monetary Communications for IoT Forum
9.3 Privacy in Blockchain Related Work
9.4 Initial Preparations
9.4.1 Blockchain Overview
9.4.2 k-Anonymity
9.4.2.1 Degree of Anonymity
9.4.2.2 Data Forfeiture
9.5 In the IoT Power and Service Markets, Reliable Transactions and Billing
9.5.1 Connector or Bridge
9.5.2 Group of Credit-Sharing
9.5.3 Local Block
9.6 Potential Applications and Use Cases
9.6.1 Utilities and Energy
9.6.2 Charging of Electric Vehicles
9.6.3 Credit Transfer
9.7 Proposed Work Execution
9.7.1 Creating the Group of Energy Sharing
9.7.2 Handling of Transaction
9.8 Investigation of Secrecy and Trustworthy
9.8.1 Trustworthy
9.8.2 Privacy-Protection
9.8.2.1 Degree of Confidentiality
9.8.2.2 Data Forfeiture
9.8.3 Evaluation of Results
9.9 Conclusion
References
10. IoTSG in Maintenance Management
T.C. Kalaiselvi and C.N. Vanitha
10.1 Introduction to the Chapter
10.2 IoT in Smart Grid
10.2.1 Uses and Facilities in SG
10.2.2 Architectures in SG
10.3 IoT in the Generation Level, Transmission Level, Distribution Level
10.4 Challenges and Future Research Directions in SG
10.5 Components for Predictive Management
10.6 Data Management and Infrastructure of IoT for Predictive Management
10.6.1 PHM Algorithms for Predictive Management
10.6.2 Decision Making with Predictive Management
10.7 Research Challenges in the Maintenance of Internet of Things
10.8 Summary
References
11. Intelligent Home Appliance Energy Monitoring with IoT
S. Tamilselvan, D. Deepa, C. Poongodi, P. Thangavel and Sarumathi Murali
11.1 Introduction
11.2 Survey on Energy Monitoring
11.3 Internet of Things System Architecture
11.4 Proposed Energy Monitoring System with IoT
11.5 Energy Management Structure (Proposed)
11.6 Implementation of the System
11.6.1 Implementation of IoT Board
11.6.2 Software Implementation
11.7 Smart Home Automation Forecasts
11.7.1 Energy Measurement
11.7.2 Periodically Updating the Status in the Cloud
11.7.3 Irregularity Detection
11.7.4 Finding the Problems with the Device
11.7.5 Indicating the House Owner About the Issues
11.7.6 Suggestions for Remedial Actions
11.8 Energy Reduction Based on IoT
11.8.1 House Energy Consumption (HEC) - Cost Saving
11.9 Performance Evaluation
11.9.1 Data Analytics and Visualization
11.10 Benefits for Different User Categories
11.11 Results and Discussion with Benefits of User Categories
11.12 Summary
References
12. Applications of IoTSG in Smart Industrial Monitoring Environments
Mohanasundaram T., Vetrivel S.C., and Krishnamoorthy V.
12.1 Introduction
12.2 Energy Management
12.3 Role of IoT and Smart Grid in the Banking Industry
12.3.1 Application of IoT in the Banking Sector
12.3.1.1 Customer Relationship Management (CRM)
12.3.1.2 Loan Sanctions
12.3.1.3 Customer Service
12.3.1.4 Leasing Finance Automation
12.3.1.5 Capacity Management
12.3.2 Application of Smart Grid in the Banking Sector
12.4 Role of IoT and Smart Grid in the Automobile Industry
12.4.1 Application of IoT in the Automobile Industry
12.4.1.1 What Exactly is the Internet of Things (IoT) Mean to the Automobile Sector?
12.4.1.2 Transportation and Logistics
12.4.1.3 Connected Cars
12.4.1.4 Fleet Management
12.4.2 Application of Smart Grid (SG) in the Automobile Industry
12.4.2.1 Smart Grid Can Change the Face of the Automobile Industry
12.4.2.2 Smart Grid and Energy Efficient Mobility System
12.5 Role of IoT and SG in Healthcare Industry
12.5.1 Applications of IoT in Healthcare Sector
12.5.2 Application of Smart Grid (SG) in Health Care Sector
12.6 IoT and Smart Grid in Energy Management - A Way Forward
12.7 Conclusion
References
13. Solar Energy Forecasting for Devices in IoT Smart Grid
K. Tamil Selvi, S. Mohana Saranya and R. Thamilselvan
13.1 Introduction
13.2 Role of IoT in Smart Grid
13.3 Clear Sky Models
13.3.1 REST2 Model
13.3.2 Kasten Model
13.3.3 Polynomial Fit
13.4 Persistence Forecasts
13.5 Regressive Methods
13.5.1 Auto-Regressive Model
13.5.2 Moving Average Model
13.5.3 Mixed Auto Regressive Moving Average Model
13.5.4 Mixed Auto Regressive Moving Average Model with Exogeneous Variables
13.6 Non-Linear Stationary Models
13.7 Linear Non-Stationary Models
13.7.1 Auto Regressive Integrated Moving Average Models
13.7.2 Auto-Regressive Integrated Moving Average Model with Exogenous Variables
13.8 Artificial Intelligence Techniques
13.8.1 Artificial Neural Network
13.8.2 Multi-Layer Perceptron
13.8.3 Deep Learning Model
13.8.3.1 Stacked Auto-Encoder
13.8.3.2 Deep Belief Network
13.8.3.3 Deep Recurrent Neural Network
13.8.3.4 Deep Convolutional Neural Network
13.8.3.5 Stacked Extreme Learning Machine
13.8.3.6 Generative Adversarial Network
13.8.3.7 Comparison of Deep Learning Models for Solar Energy Forecast
13.9 Remote Sensing Model
13.10 Hybrid Models
13.11 Performance Metrics for Forecasting Techniques
13.12 Conclusion
References
14. Utilization of Wireless Technologies in IoTSG for Energy Monitoring in Smart Devices
S. Suresh Kumar, A. Prakash, O. Vignesh and M. Yogesh Iggalore
14.1 Introduction to Internet of Things
14.2 IoT Working Principle
14.3 Benefits of IoT
14.4 IoT Applications
14.5 Introduction to Smart Home
14.5.1 Benefits of Smart Homes
14.6 Problem Statement
14.6.1 Methodology
14.7 Introduction to Wireless Communication
14.7.1 Merits of Wireless
14.8 How Modbus Communication Works
14.8.1 Rules for Modbus Addressing
14.8.2 Modbus Framework Description
14.8.2.1 Function Code
14.8.2.2 Cyclic Redundancy Check
14.8.2.3 Data Storage in Modbus
14.9 MQTT Protocol
14.9.1 Pub/Sub Architecture
14.9.2 MQTT Client Broker Communication
14.9.3 MQTT Standard Header Packet
14.9.3.1 Fixed Header
14.10 System Architecture
14.11 IoT Based Electronic Energy Meter-eNtroL
14.11.1 Components Used in eNtroL
14.11.2 PZEM-004t Energy Meter
14.11.3 Wi-Fi Module
14.11.4 Switching Device
14.11.5 230V AC to 5V Dc Converter
14.11.6 LM1117 IC- 5V to 3.3V Converter
14.12 AC Control System for Home Appliances – Switch2Smart
14.12.1 Opto-Coupler- H11AA1 IC
14.12.2 TRIAC Driven Opto Isolator- MOC3021M IC
14.12.3 TRIAC, BT136-600 IC
14.13 Scheduling Home Appliance Using Timer – Switch Binary
14.14 Hardware Design
14.14.1 Kaicad Overview
14.14.2 PCB Designing Using Kaicad
14.14.2.1 Designing of eNtroL Board Using Kaicad
14.14.2.2 Designing of Switch2smart Board Using Kaicad
14.14.2.3 Designing of Switch Binary Board Using Kaicad
14.15 Implementation of the Proposed System
14.16 Testing and Results
14.16.1 Testing of eNtrol
14.16.2 Testing of Switch2Smart
14.16.3 Testing of SwitchBinary
14.17 Conclusion
References
15. Smart Grid IoT: An Intelligent Energy Management in Emerging Smart Cities
R. S. Shudapreyaa, G. K. Kamalam, P. Suresh and K. Sentamilselvan
15.1 Overview of Smart Grid and IoT
15.1.1 Smart Grid
15.1.2 Smart Grid Data Properties
15.1.3 Operations on Smart Grid Data
15.2 IoT Application in Smart Grid Technologies
15.2.1 Power Transmission Line - Online Monitoring
15.2.2 Smart Patrol
15.2.3 Smart Home Service
15.2.4 Information System for Electric Vehicle
15.3 Technical Challenges of Smart Grid
15.3.1 Inadequacies in Grid Infrastructure
15.3.2 Cyber Security
15.3.3 Storage Concerns
15.3.4 Data Management
15.3.5 Communication Issues
15.3.6 Stability Concerns
15.3.7 Energy Management and Electric Vehicle
15.4 Energy Efficient Solutions for Smart Cities
15.4.1 Lightweight Protocols
15.4.2 Scheduling Optimization
15.4.3 Energy Consumption
15.4.4 Cloud Based Approach
15.4.5 Low Power Transceivers
15.4.6 Cognitive Management Framework
15.5 Energy Conservation Based Algorithms
15.5.1 Genetic Algorithm (GA)
15.5.2 BFO Algorithm
15.5.3 BPSO Algorithm
15.5.4 WDO Algorithm
15.5.5 GWDO Algorithm
15.5.6 WBFA Algorithm
15.6 Conclusion
References
Index

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