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Submit a ProposalEnergy |
Cyber Physical Energy Systems
 | Edited by Shrddha Sagar, T. Poongodi, Rajesh Kumar Dhanaraj, and Sanjeevikumar Padmanaban Copyright: 2025 | Expected Pub Date:2024// ISBN: 9781394172528 | Hardcover | 556 pages Price: $225 USD  |
One Line Description
This book is essential for understanding the transformative integration of cyber-physical systems in smart grids, providing valuable insights that will shape the future of sustainable energy production and distribution.
Audience
Professionals in the energy sector, researchers and application developers of cyber physical systems, undergraduate and postgraduate students exploring trends in the Internet of Energy, and professionals in smart manufacturing and Industry 4.0
Professionals in the energy sector, researchers and application developers of cyber physical systems, undergraduate and postgraduate students exploring trends in the Internet of Energy, and professionals in smart manufacturing and Industry 4.0
Description
A novel modeling methodology that blends cyber and physical components is a significant advancement for future energy systems. A Cyber-Physical System (CPS) is an integrated component of physical microgrids that combines computers, wireless connections, and controls to create a holistic solution. As a result of cyber-physical systems, a new generation of engineering systems incorporating wireless communication has begun to emerge. Despite that there are various major CPS systems in use today, one of the most challenging sectors for implementation is the smart grid which aims to distribute dependable and efficient electric energy while maintaining a high level of global environmental sustainability.
Electric networks that incorporate sophisticated monitoring are known as smart grids, and these networks ensure a consistent and secure energy supply while increasing the efficiency of generators and distributors and providing consumers with more choices. The smart grid attempts to increase energy systems capacities and reactivity in the areas of production, transmission, distribution, and consumption, while the cyber issue is concerned with the power grids ability to regulate and monitor physical behavior in a safe and efficient manner. In the coming years, these research concerns, as well as the development of successful design architectures, will be a subject of controversy for the research community. The interface between traditional engineering areas and computer science is critical to CPS research and development. With the emergence of dispersed and renewable energy sources, however, this situation is changing. Tried-and-true methods are being questioned, necessitating change, as well as the cross-domain integration of energy systems and well as the integration of large amounts of data. Cyber Physical Energy Systems presents explanations of the architectures, as well as methods for integrating this state-of-the-art technology into the power grid for more sustainable energy production and dispersal.
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A novel modeling methodology that blends cyber and physical components is a significant advancement for future energy systems. A Cyber-Physical System (CPS) is an integrated component of physical microgrids that combines computers, wireless connections, and controls to create a holistic solution. As a result of cyber-physical systems, a new generation of engineering systems incorporating wireless communication has begun to emerge. Despite that there are various major CPS systems in use today, one of the most challenging sectors for implementation is the smart grid which aims to distribute dependable and efficient electric energy while maintaining a high level of global environmental sustainability.
Electric networks that incorporate sophisticated monitoring are known as smart grids, and these networks ensure a consistent and secure energy supply while increasing the efficiency of generators and distributors and providing consumers with more choices. The smart grid attempts to increase energy systems capacities and reactivity in the areas of production, transmission, distribution, and consumption, while the cyber issue is concerned with the power grids ability to regulate and monitor physical behavior in a safe and efficient manner. In the coming years, these research concerns, as well as the development of successful design architectures, will be a subject of controversy for the research community. The interface between traditional engineering areas and computer science is critical to CPS research and development. With the emergence of dispersed and renewable energy sources, however, this situation is changing. Tried-and-true methods are being questioned, necessitating change, as well as the cross-domain integration of energy systems and well as the integration of large amounts of data. Cyber Physical Energy Systems presents explanations of the architectures, as well as methods for integrating this state-of-the-art technology into the power grid for more sustainable energy production and dispersal.
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Author / Editor Details
Shrddha Sagar, PhD is a professor in the School of Computing Science and Engineering, Galgotias University, India with more than 14 years of experience working in teaching and research. She is the author of over ten book chapters and over 25 international journals and conferences. In her research, she has undertaken meticulous scientific studies of emerging issues in several disciplines including artificial intelligence, Internet of Things, machine learning, and big data.
Shrddha Sagar, PhD is a professor in the School of Computing Science and Engineering, Galgotias University, India with more than 14 years of experience working in teaching and research. She is the author of over ten book chapters and over 25 international journals and conferences. In her research, she has undertaken meticulous scientific studies of emerging issues in several disciplines including artificial intelligence, Internet of Things, machine learning, and big data.
T. Poongodi, PhD is a professor in the School of Computing Science and Engineering at the Galgotias University, India. She is the author of over 40 book chapters, over 30 international journals and conferences, and over 10 books. In her research, she has undertaken meticulous scientific studies of emerging issues in several disciplines including network security, wireless ad hoc and sensor networks, Internet of Things (IoT), computer networks, and blockchain technology for emerging communication networks. She is a member of The Institute of Electrical and Electronics Engineers (IEEE), IEEE Women in Engineering, Association for Computing Machinery, International Association of Engineers, Institute of Research Engineers and Doctors, and the International Association of Computer Science and Information Technology.
Rajesh Kumar Dhanaraj, PhD is a professor in the School of Computing Science and Engineering at Galgotias University, India. He has contributed to over 25 books on various technologies, has 21 Patents, and has authored 53 articles and papers in various refereed journals and international conferences, as well as chapters in books. He is a Senior Member of the Institute of Electrical and Electronics Engineers and a member of the Computer Science Teacher Association and International Association of Engineers, as well as an expert advisory panel member of Texas Instruments Inc., USA.
P. Sanjeevikumar is a chartered engineer in the Institution of Engineers, India. His research work is focused on the field of power electronics and drives and includes multi-phase machines, multilevel and DC-DC converters, and applications of renewable power generation systems. He has authored over 250 scientific research papers and is involved as a member in various capacities on the committees for more than 4500 international conferences, including the Institute of Electrical and Electronics Engineers and Institution of Engineering and Technology.
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Table of Contents
Preface
1. Cyber-Physical Systems: A Control and Energy Approach
Shaik Mahaboob Basha, Gajanan Shankarrao Patange, V. Arulkumar, J. V. N. Ramesh and A. V. Prabu
1.1 Introduction
1.1.1 Background and Motivation
1.1.2 Testbeds, Revisions, and a Safety Study for Cyber‑Physical Energy Systems
1.1.3 CPES Test Chamber
1.1.4 Significance and Contributions of Testbed
1.1.5 Testbed Setup
1.1.6 Illustration of Hybrid CPES Testbed Structure
1.2 Studies on CPES Safety
1.2.1 Attacks in the CPES System
1.2.2 Evaluation of Attack Impacts on CPES
1.2.3 CPES’s Assault Detection Algorithms
1.2.4 CPES’s Assault Mitigation and Defense Systems
1.2.5 Dangerous Imagery
1.2.6 Attack Database
1.3 Threat Evaluation
1.4 Theory of Cyber-Physical Systems Risk
1.4.1 Challenger Type
1.4.2 Attack Type
1.5 Threat Evaluation Methodology
1.5.1 Cyber-System Layer
1.5.2 Physical-System Layer
1.6 Experimental Setup for Cross-Layer Firmware Threats
1.6.1 Risk Model
1.6.2 Threat Evaluation
1.7 Conclusion
References
2. Optimization Techniques for Energy Management in Microgrid
Shenbaga Bharatha Priya A., Indra Singh Bisht, N. Balambigai, Sumit Kataria and R. Ramalakshmi
2.1 Introduction
2.1.1 Microgrid Systems
2.1.2 Energy Management System
2.1.3 Energy Management of Distribution System
2.1.4 Techniques to Take Into Account While Implementing the EMS
2.1.5 Strategies for Reducing Risk
2.1.6 Monitoring Power Systems
2.1.7 Demand Response, Price Strategy, and Demand Side Management
2.2 Explanation Methods for EMS
2.3 EQN EMS on an Arithmetic Optimization Basis
2.4 Heuristic-Oriented Methods to EMS Problem-Solving
2.5 EMS Solution Techniques Using Meta-Heuristics
2.6 Alternative EMS Implementation Strategies
2.6.1 SCADA System
2.7 Conclusion and Viewpoints
References
3. Cyber-Physical Energy Systems for Smart Grid: Reliable Distribution
Jyoti Parashar, A. Devipriya, R. Lokeshkumar, J.V.N. Ramesh and Arindam Pal
3.1 Introduction
3.1.1 Need for Sustainable and Efficient Power Generation Through Smart Grid Technology and Cyber-Physical Technologies
3.1.2 CPES: The Integration of Physical and Digital Worlds
3.2 Cyber-Physical Energy Systems (CPES)
3.3 Forming Energy Systems
3.4 Energy Efficiency
3.4.1 CPES Usage on Smart Grids
3.5 Smart Grids
3.6 Cyber-Physical Systems
3.7 SG: A CPS Viewpoint
3.7.1 Challenges and Solutions for Coordinating Smart Grids and Cyber-Physical Systems
3.7.2 Techniques of Correspondence
3.7.3 Data Protection
3.7.4 Data Skill and Engineering
3.7.5 Distributed Computation
3.7.6 Distributed Intellect
3.7.7 Distributed Optimization
3.7.8 Distributed Controller
3.8 Upcoming Prospects and Contests
3.8.1 Big Data
3.8.2 Cloud Computing
3.8.3 IoT
3.8.4 Network Science
3.8.5 Regulation and Guidelines
3.9 Conclusion
References
4. Evolution of AI in CPS: Enhancing Technical Capabilities and Human Interactions
Namya Musthafa, P. Suresh and Yazid Musthafa
4.1 Introduction to Cyber-Physical System
4.2 The Cyber-Physical Systems Architecture
4.2.1 5C Architecture or CPS
4.2.1.1 Connection
4.2.1.2 Conversion
4.2.1.3 Cyber
4.2.1.4 Knowledge
4.2.1.5 Configuration
4.3 Cyber-Physical Systems as Real-Time Applications
4.3.1 Robotics Distributed
4.3.2 Manufacturing
4.3.3 Distribution of Water
4.3.4 Smart Greenhouses
4.3.5 Healthcare
4.3.6 Transportation
4.4 Impact of AI on Cyber-Physical Systems
4.5 Policies
4.6 Expected Benefits and Core Promises
4.7 Unintended Consequences and Implications for Policy
4.7.1 Negative Social Impacts
4.7.2 Cybersecurity Risks
4.7.3 Impact on the Environment
4.7.4 Ethical Issues
4.7.5 Policy Implications
4.8 Employment and Delegation of Tasks
4.9 Safety, Responsibility, and Liability
4.10 Privacy Concerns
4.10.1 Data Collection and Use
4.10.2 Data Security
4.10.3 Data Sharing
4.10.4 Bias and Discrimination
4.10.5 User Empowerment
4.11 Social Relations
4.11.1 Cyber-Physical Systems and Transport
4.11.2 Trade of Dual-Use Technology
4.11.3 Civil Liberties (Data Protection, Privacy, etc.)
4.11.4 Safety (Such as Risk Analysis, Product Safety, etc.)
4.11.5 Healthcare (Medical Devices, Clinical Trials, and E-Health Devices)
4.11.6 Energy and Environment
4.11.7 Horizontal Legal Issues (Cross-Committee Considerations)
4.12 Economic Study on CPS
4.12.1 Better Resource Allocation
4.12.2 Enhanced Marketability
4.12.3 Robustness and Resilience
4.12.4 Regulatory Compliance
4.12.5 Making Decisions in Real-Time
4.13 Case Studies
4.13.1 The Daily Lives of Older Persons and Disabled Individuals with CPS
4.13.2 CPS in Healthcare
4.13.3 CPS for Security and Safety
4.14 Conclusion
References
5. IoT Technology Enables Sophisticated Energy Management in Smart Factory
Deependra Rastogi, Prashant Johri, Swati Verma, Vanita Garg and Hradesh Kumar
5.1 Introduction
5.2 IOT Overview
5.2.1 The Evolution of the Internet
5.2.2 IoT Sensing
5.2.3 IOT Data Protocol and Architecture
5.3 IOT Enabling Technology
5.3.1 Application Domain
5.3.2 Middleware Domain
5.3.3 Network Domain
5.3.4 Object Domain
5.4 IOT in Energy Sector
5.4.1 Internet of Things and Energy Generation
5.5 Challenges of Applying IOT
5.6 Reference Architecture for IoT-Based Smart Factory
5.7 Characteristics of Smart Factory
5.8 Challenges for IoT-Based Smart Industry
5.9 How IoT Will Support Energy Management in Smart Factory
5.10 IoT Energy Management Architecture for Industrial Applications
5.10.1 IoT-Based Energy Management Technology
5.10.2 Energy Harvesting
5.11 Case Study: Smart Factory
5.11.1 Supply Side
5.11.2 Photovoltaic Power Generation
5.11.3 Smart Micro-Grid
5.11.4 Demand Side
5.11.5 Virtualization
5.12 Conclusion
References
6. IOT-Based Advanced Energy Management in Smart Factories
M. Nalini, Dhanashree Varadharajan, Nithyashree Natarajan and Yogabhuvaneswari Umasankar
6.1 Introduction
6.2 Smart Factory Benefits of IOT-Based Advanced Energy Management
6.3 Role of IOT Technology in Energy Management
6.4 Developing an IOT Information Model for Energy Efficiency
6.5 Integrating Intelligent Energy Systems (IES) and Demand Response (DR)
6.6 How to Accurately Measure and Manage Your Energy Usage
6.7 Introduction to Energy Efficiency Measures
6.8 Identifying Opportunities to Reduce Energy Use
6.9 Monitoring and Measuring Energy Usage
6.10 Establishing Accounting and Incentives
6.11 Sustaining the Long-Term Benefits of Optimized Energy Usage
6.12 Role of Cyber Security When Implementing IoT-Based Advanced Energy Solutions
6.13 Materials Required in Smart Factories
6.14 Methods in IoT-Based Smart Factory Implementation
6.15 Steps for Developing an IoT-Based Energy Management System
6.15.1 Assess Current Energy Usage
6.15.2 Develop an Energy Conservation Plan
6.15.3 Implement IoT Technology
6.15.4 Monitor Results
6.16 Challenges For Adopting IoT-Based Energy Management Systems
6.16.1 Big Data and Analytics
6.16.2 Connectivity Constraints
6.16.3 Data Security and Privacy Issues
6.16.4 Device Troubleshooting
6.17 Recommendations for Overcoming the Challenges With Implementing IoT-Based Advanced Energy Solution
6.17.1 IoT-Enabled Automation
6.17.2 Smart Sensors
6.17.3 Predictive Analytics
6.18 Case Studies
6.18.1 Automated Demand Response (ADR)
6.18.2 Automated Maintenance
6.18.3 Predictive Analytics
6.19 Case Studies for Successful Implementation
6.20 Applications
6.21 Different Techniques for Monitoring and Control of IoT Devices
6.22 Literature Survey
6.23 Conclusion
References
7. Challenges in Ensuring Security for Smart Energy Management Systems Based on CPS
V. M. Meera and K. P. Arjun
7.1 Introduction
7.1.1 Brief Overview of Smart Energy Management Systems and Cyber-Physical Systems
7.1.2 Importance of Security in CPS-Based Smart Energy Management
7.2 Cyber-Physical Systems and Smart Energy Management
7.2.1 CPS Architecture and Components
7.2.2 Types of CPS-Based Smart Energy Management Systems
7.2.3 Common Communication Protocols Used in CPS-Based Smart Energy Management
7.2.4 Cyber Security Threats in CPS-Based Systems
7.3 Security Challenges in CPS-Based Smart Energy Management
7.3.1 Cyber Security Threats to CPS-Based Smart Energy Management Systems
7.3.2 Vulnerabilities of Communication Protocols Used in Smart Energy Management
7.3.3 Attack Vectors for Compromising CPS-Based Smart Energy Management Systems
7.4 Cyber Security Standards and Guidelines for Smart Energy Management
7.4.1 Cyber Security Incidents in Smart Energy Management
7.5 Conclusion
References
8. Security Challenges in CPS-Based Smart Energy Management
Lucia Agnes Beena T., Vinolyn Vijaykumar and Mercy P.
8.1 Introduction
8.2 CPS Architecture
8.3 The Driving Forces for CPS
8.3.1 Big Data
8.3.2 Cloud
8.3.3 Machine-to-Machine Communication and Wireless Sensor Networks
8.3.4 Mechatronics
8.3.5 Cybernetics
8.3.6 Systems of Systems
8.4 Advances in Cyber-Physical Systems
8.4.1 Application Domains of CPS
8.4.1.1 Industrial Transformation
8.4.1.2 Smart Grid
8.4.1.3 Healthcare
8.4.1.4 Smart Parking System
8.4.1.5 Household CPS
8.4.1.6 Aerospace
8.4.1.7 Agriculture
8.4.1.8 Construction
8.5 Energy Management through CPS
8.5.1 Energy Management of CPS for Smart Grid
8.5.2 Energy Management of CPS for Smart Building Structure
8.5.3 Energy Management of CPS for Autonomous Electric Vehicles in Smart Transportation
8.5.4 Energy Management of CPS for Smart Industry
8.5.5 Energy Management of CPS for Home Automation
8.6 Security Issues in CPS
8.6.1 Threats
8.6.1.1 Cyber Threats
8.6.1.2 Physical Threats
8.6.2 CPS Vulnerabilities
8.6.3 CPS Attacks
8.6.4 CPS Failures
8.6.5 Risk Identification and Management
8.6.6 Protecting CPS
8.6.7 Security Solutions for CPS
8.7 Open Challenges and Future Directions
8.7.1 Open Challenges
8.7.1.1 Infrastructure Challenges
8.7.1.2 Network Communication Challenges
8.7.1.3 Control Operational and Computational Challenges
8.7.1.4 CPS Deployment Challenges
8.7.2 Future Directions
8.8 Conclusion
References
9. Blockchain-Based Energy Transmission System: Design, Optimization, and Data-Driven Modeling
Prabha Selvaraj, Rohit Kumar Das, Vijay Kumar Burugari, Ganesh Reddy Karri, Kanmani P. and Anupama Namburu
9.1 Introduction
9.2 Literature Review
9.2.1 Essential Parts of a Blockchain Include
9.2.2 Blockchain and Smart Agreements
9.2.2.1 Blockchain 3.0 Scalability and Interoperability
9.2.2.2 Interoperability
9.2.2.3 Blockchain 4.0 Scalability
9.2.2.4 Energy Efficiency
9.2.2.5 Possible Solutions
9.3 Case Study and Application
9.3.1 Energy Transmission Monitoring with Advanced Metering Infrastructure
9.3.2 Energy Optimization with Home Automation
9.3.3 Renewable Microgrids
9.3.4 Blockchain for Electric Vehicles
9.4 Conclusion
References
10. Explainable AI Technology in E-CPS: Policy Design, Economic Research, and Case Studies
Thangaraja Arumugam, Saritha Bantu, Yeligeti Raju, Renuka Deshmukh and B. Raja Mannar
10.1 Introduction
10.1.1 Terminology
Nomenclature
10.2 E-CPS Arrangement
10.2.1 E-CPS Framework
10.3 Case Study: Method Depiction
10.3.1 Fixing Constraints
10.3.2 Information Preparation
10.3.3 Prediction Framework
10.3.4 Controlling Approach
10.3.5 Result Analysis
10.3.6 Overview
10.4 Transformation of the Power Infrastructure
10.4.1 Cyber-Physical System
10.4.2 Power Effectiveness—Cumulative Power Efficacy
10.5 Power Managing Structures
10.5.1 Following that are Some Notable Instances of How CPS Affects Power Sources
10.5.2 Data Analysis
10.5.3 Utilising Agent-Based Modelling and Linear Optimization for Improved Urban Planning
10.5.4 Enhancing Compatibility and Utilization of e-CPS Components for Improved Administration of Commercial Structures
10.5.5 e-CPS Effects on the Power Change
10.5.6 Policies Involved and Economics Research
10.6 Protection Policies
10.7 Urgent Need for Effective Governance of AI and e-CPS
10.8 Conclusions
References
11. Infrastructural Data Visualization and Improved User Interfaces of Energy Consumption in Smart Cities
Prabha Selvaraj, Kanmani P., T.Y.J. Naga Malleswari, Vijay Kumar Burugari and S. Sudheer Mangalampalli
11.1 Introduction
11.1.1 Internet of Things (IoT)
11.1.2 Big Data
11.1.3 Cloud Computing
11.1.3.1 Infrastructure in Smart City
11.1.3.2 Types of Smart Infrastructure
11.1.4 Issues with Smart City Infrastructure
11.1.4.1 Organizational Issues
11.1.4.2 Data Quality and Collection Issues
11.1.4.3 Governance and Privacy Issues
11.1.4.4 Maintenance and Durability
11.2 Literature Review
11.3 Visualization Tools and Interfaces Used in Smart Cities Using IoT
11.4 Energy Representation Frameworks
11.5 Materials and Methods
11.5.1 Smart Cities and Energy Consumption
11.5.1.1 Active Approach
11.5.1.2 Passive Approach
11.5.2 Importance of Energy-Efficient in Sustainable Buildings
11.5.3 Energy Consumption and Management in Smart Cities
11.5.4 Materials and Strategies
11.5.4.1 Requirements and Work Processes
11.5.4.2 Data Collection
11.5.5 Visual Encoding and Communication Plan
11.5.5.1 Map and Local Area Wayfarer
11.5.5.2 Scatterplot and Examination Diagram
11.6 Case Study and Applications
11.6.1 Functionalities of the Energy Hub Platform
11.6.1.1 Mechanisms of the Energy Conservation for Smart Cities
11.6.1.2 Smart Electricity Grids for Smart Cities
11.6.1.3 Data Visualization and Its Importance in Smart Cities
11.6.1.4 Security Challenges in Smart City
11.6.1.5 Smart Transportation and Smart Traffic Management
11.6.1.6 Domestic Renewable Energy System Integration in Cities
11.7 Factors for the Improvement of Energy Efficacy in Smart Cities
11.7.1 Prediction of Electrical Consumption in Smart Cities
11.8 Conclusion and Future Scope
References
12. Power Management in Intelligent Buildings Based on Daily Demand Prediction
V. Geethapriya, D. Sivamani, D. Shyam, A. Sangari, M. Manish, Prasheetha and Divina Julia
12.1 Introduction
12.1.1 Summary from Introduction
12.2 The Power Management System Block Diagram
12.3 Working Task of Power Management System
12.4 Simulation Model of Power Management System
12.5 Hardware Implementation of Power Management System
12.6 Safety Precautions in Smart Building Implementation
12.7 Conclusion
References
13. Schemes and Security Attacks on the Integrity of Cyber-Physical Systems in Energy Systems
Rajesh Kumar, Charanjeet Singh, Yeligeti Raju, Pratap Patil and K. Saravanan
13.1 Introduction
13.1.1 CPS Protection Purposes
13.1.2 Confidentiality
13.1.3 Authenticity
13.1.4 Accessibility
13.1.5 Resilience
13.1.6 Trustworthiness
13.2 CPS Safety Methodologies
13.2.1 Threat Categorisation
13.2.2 Spying
13.2.3 Sneaky Deceit Assault
13.2.4 Attack Using a Vulnerable Key
13.2.5 Assault on the Centre Spy
13.2.6 Jamming Assault
13.2.7 Replay Attack
13.2.8 Refusal of Package Assault
13.2.9 Assault Demonstrating
13.2.10 Assault Sensing
13.2.11 Safety Resolutions
13.2.12 Construction and Designing for Protection
13.2.13 Safety in Definite CPS
13.2.14 Energy System Safety
13.2.15 Medicinal CPS Safety
13.2.16 Portable CPS Safety
13.2.17 Motorised CPS Safety
13.3 Shielding in Contradiction of Information Safety Assaults
13.3.1 Enhancing Data Security in the Electricity System Through a Markov Decision Process (MDP)
13.3.2 Evaluating the Effectiveness of a Determination Method for Data Security Assaults in Power Systems
13.4 Scheme Variants
13.4.1 Assault Variant
13.5 Supervised Learning in Depth
13.5.1 DQND Scheme
13.5.2 Assault Situations
13.5.3 Markov Resolution Concepts
13.5.4 Assessment Spatial and Sliding Windows Measurements
13.5.5 DQND Scheme
13.5.6 System Education
13.5.7 Efficiency Assessment
13.5.8 Algorithm 1: Education Phase of DQND
13.5.9 Algorithm 2: Evaluation Phase of DQND
13.5.10 Assessment Metrics
13.5.11 Standards
13.6 Discussion
13.7 Conclusion
References
14. Adaptive Power System Resource Management in Cyber-Physical Energy Systems
Virendra Singh Kushwah, Indra Singh Bisht, Charanjeet Singh, K. Gurnadha Gupta and K. Suresh
14.1 Introduction
14.1.1 Modelling and Simulation of CPES for Integrating Data Networks with Electricity Networks
14.1.2 Actual-Period Energy Network Modelling and Simulation using RTLAB and OPNET Modeller with SITL Integration
14.1.3 Cyber Attack on Ukraine’s Power Grid in 2015: Incident Overview and Implications for Critical Infrastructure Security
14.1.4 CPES Sensitivity Evaluation Process Utilising Virtualized CP Linkages
14.2 CPES Structures
14.2.1 Diversified
14.2.2 Self Determination
14.2.3 Actual Period
14.2.4 Reconstitute
14.2.5 Consistency
14.2.6 Intensely Encapsulated
14.3 Development of CPES Structures
14.3.1 Assistances of Cyber-Physical Energy System
14.3.2 CPES Difficulties
14.3.3 CPES Forming
14.3.4 Computer Estimation of the Variability of the Network
14.4 Resource Management in Socio-CPS
14.5 Associated Study
14.5.1 Assessment of CP Multilateral Implications
14.6 The Integrated Modelling Platform for the CPES
14.6.1 Nodal Junction
14.6.2 PP Linkages
14.6.3 Nodal Junctions
14.6.4 CP Linkage
14.7 Assault from Without and Compounding Collapse
14.7.1 Procedure for Appropriate Load Diminishment
14.8 The Combination of Assault and Defence
14.8.1 Issues with Bi-Level Computing
14.8.2 Defence of Resource Allocation
14.8.3 Methodology for Security Testing
14.9 Case Studies
14.10 Conclusions and Future Work
References
15. Cyber-Physical Energy Systems for Electric Vehicles
ShaikMahaboob Basha, Akilandeswari P., Suguna M., Prakash D., Biruntha S. and Vivekanandan P.
15.1 Introduction
15.1.1 Smart-Use CPESs of Emerging Technologies for Sustainable Energy Solutions
15.1.2 Technology for Power Storage and Fuel Cells for CPES in EVS
15.1.3 Vehicle Cyber-Physical Energy Systems: Problems and Implications
15.1.4 Electric Drive-Train
15.1.5 Managing Storage Units (Batteries)
15.1.6 Dispersed Managing Batteries
15.2 Suggested Type
15.2.1 Activity Tracking Technique Deployment in CPES Using Electro-Mechanical Connections
15.2.2 MPSSU uses Ultra-Capacitors for Higher Energy Distribution and Rapid Power Outages
15.3 Outcomes from Experiments and Simulations
15.3.1 Modeling the DC Bus Network for SCPEDS Using the Port-Hamiltonian Approach
15.3.2 Electric Vehicle Energy Conversion and Inversion Simulation using the PSIM Program
15.3.3 Additional Energy Management Techniques Explored in Studies
15.4 Discussion
15.4.1 Power-Controlling and Autonomous Vehicle Diagnosis Using Genetic Algorithms (GAs)
15.5 Conclusion
References
16. Design and Implementation of IoT‑Based Advanced Energy Management System for Smart Factory
S. Jayanthi, N. Suresh Kumar, Zafar Ali Khan N., S. Sreenatha Reddy, R. Santhosh and Pachipala Yellamma
16.1 Introduction
16.1.1 Driving Factors
16.1.2 Industry 5.0
16.1.3 Smart Metres
16.2 Challenges Faced by Factories Today
16.2.1 How Do Businesses Try to Get Over the Obstacles That Exist in Their Manufacturing Plants?
16.2.2 Prospects of Industrial IoT
16.2.3 Impact of IoT on Smart Factories
16.3 Home Energy Management Systems (HEMSs)
16.4 Micro Grid for Integration of Several Sources and Storage
16.4.1 Deming Cycle
16.4.2 Setbacks of Effective Smart Energy Systems
16.4.3 Essential Sensing Technologies in Smart Factories
16.4.4 Four Cognitive Facets Define a Smart Factory
16.4.5 Reasons Why Industries Need to Fully Utilise IoT’s Benefits
16.5 Proposed Robust Energy Management System for Smart Factories
16.6 Conclusion
16.7 Future Trends
References
Index
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Preface
1. Cyber-Physical Systems: A Control and Energy Approach
Shaik Mahaboob Basha, Gajanan Shankarrao Patange, V. Arulkumar, J. V. N. Ramesh and A. V. Prabu
1.1 Introduction
1.1.1 Background and Motivation
1.1.2 Testbeds, Revisions, and a Safety Study for Cyber‑Physical Energy Systems
1.1.3 CPES Test Chamber
1.1.4 Significance and Contributions of Testbed
1.1.5 Testbed Setup
1.1.6 Illustration of Hybrid CPES Testbed Structure
1.2 Studies on CPES Safety
1.2.1 Attacks in the CPES System
1.2.2 Evaluation of Attack Impacts on CPES
1.2.3 CPES’s Assault Detection Algorithms
1.2.4 CPES’s Assault Mitigation and Defense Systems
1.2.5 Dangerous Imagery
1.2.6 Attack Database
1.3 Threat Evaluation
1.4 Theory of Cyber-Physical Systems Risk
1.4.1 Challenger Type
1.4.2 Attack Type
1.5 Threat Evaluation Methodology
1.5.1 Cyber-System Layer
1.5.2 Physical-System Layer
1.6 Experimental Setup for Cross-Layer Firmware Threats
1.6.1 Risk Model
1.6.2 Threat Evaluation
1.7 Conclusion
References
2. Optimization Techniques for Energy Management in Microgrid
Shenbaga Bharatha Priya A., Indra Singh Bisht, N. Balambigai, Sumit Kataria and R. Ramalakshmi
2.1 Introduction
2.1.1 Microgrid Systems
2.1.2 Energy Management System
2.1.3 Energy Management of Distribution System
2.1.4 Techniques to Take Into Account While Implementing the EMS
2.1.5 Strategies for Reducing Risk
2.1.6 Monitoring Power Systems
2.1.7 Demand Response, Price Strategy, and Demand Side Management
2.2 Explanation Methods for EMS
2.3 EQN EMS on an Arithmetic Optimization Basis
2.4 Heuristic-Oriented Methods to EMS Problem-Solving
2.5 EMS Solution Techniques Using Meta-Heuristics
2.6 Alternative EMS Implementation Strategies
2.6.1 SCADA System
2.7 Conclusion and Viewpoints
References
3. Cyber-Physical Energy Systems for Smart Grid: Reliable Distribution
Jyoti Parashar, A. Devipriya, R. Lokeshkumar, J.V.N. Ramesh and Arindam Pal
3.1 Introduction
3.1.1 Need for Sustainable and Efficient Power Generation Through Smart Grid Technology and Cyber-Physical Technologies
3.1.2 CPES: The Integration of Physical and Digital Worlds
3.2 Cyber-Physical Energy Systems (CPES)
3.3 Forming Energy Systems
3.4 Energy Efficiency
3.4.1 CPES Usage on Smart Grids
3.5 Smart Grids
3.6 Cyber-Physical Systems
3.7 SG: A CPS Viewpoint
3.7.1 Challenges and Solutions for Coordinating Smart Grids and Cyber-Physical Systems
3.7.2 Techniques of Correspondence
3.7.3 Data Protection
3.7.4 Data Skill and Engineering
3.7.5 Distributed Computation
3.7.6 Distributed Intellect
3.7.7 Distributed Optimization
3.7.8 Distributed Controller
3.8 Upcoming Prospects and Contests
3.8.1 Big Data
3.8.2 Cloud Computing
3.8.3 IoT
3.8.4 Network Science
3.8.5 Regulation and Guidelines
3.9 Conclusion
References
4. Evolution of AI in CPS: Enhancing Technical Capabilities and Human Interactions
Namya Musthafa, P. Suresh and Yazid Musthafa
4.1 Introduction to Cyber-Physical System
4.2 The Cyber-Physical Systems Architecture
4.2.1 5C Architecture or CPS
4.2.1.1 Connection
4.2.1.2 Conversion
4.2.1.3 Cyber
4.2.1.4 Knowledge
4.2.1.5 Configuration
4.3 Cyber-Physical Systems as Real-Time Applications
4.3.1 Robotics Distributed
4.3.2 Manufacturing
4.3.3 Distribution of Water
4.3.4 Smart Greenhouses
4.3.5 Healthcare
4.3.6 Transportation
4.4 Impact of AI on Cyber-Physical Systems
4.5 Policies
4.6 Expected Benefits and Core Promises
4.7 Unintended Consequences and Implications for Policy
4.7.1 Negative Social Impacts
4.7.2 Cybersecurity Risks
4.7.3 Impact on the Environment
4.7.4 Ethical Issues
4.7.5 Policy Implications
4.8 Employment and Delegation of Tasks
4.9 Safety, Responsibility, and Liability
4.10 Privacy Concerns
4.10.1 Data Collection and Use
4.10.2 Data Security
4.10.3 Data Sharing
4.10.4 Bias and Discrimination
4.10.5 User Empowerment
4.11 Social Relations
4.11.1 Cyber-Physical Systems and Transport
4.11.2 Trade of Dual-Use Technology
4.11.3 Civil Liberties (Data Protection, Privacy, etc.)
4.11.4 Safety (Such as Risk Analysis, Product Safety, etc.)
4.11.5 Healthcare (Medical Devices, Clinical Trials, and E-Health Devices)
4.11.6 Energy and Environment
4.11.7 Horizontal Legal Issues (Cross-Committee Considerations)
4.12 Economic Study on CPS
4.12.1 Better Resource Allocation
4.12.2 Enhanced Marketability
4.12.3 Robustness and Resilience
4.12.4 Regulatory Compliance
4.12.5 Making Decisions in Real-Time
4.13 Case Studies
4.13.1 The Daily Lives of Older Persons and Disabled Individuals with CPS
4.13.2 CPS in Healthcare
4.13.3 CPS for Security and Safety
4.14 Conclusion
References
5. IoT Technology Enables Sophisticated Energy Management in Smart Factory
Deependra Rastogi, Prashant Johri, Swati Verma, Vanita Garg and Hradesh Kumar
5.1 Introduction
5.2 IOT Overview
5.2.1 The Evolution of the Internet
5.2.2 IoT Sensing
5.2.3 IOT Data Protocol and Architecture
5.3 IOT Enabling Technology
5.3.1 Application Domain
5.3.2 Middleware Domain
5.3.3 Network Domain
5.3.4 Object Domain
5.4 IOT in Energy Sector
5.4.1 Internet of Things and Energy Generation
5.5 Challenges of Applying IOT
5.6 Reference Architecture for IoT-Based Smart Factory
5.7 Characteristics of Smart Factory
5.8 Challenges for IoT-Based Smart Industry
5.9 How IoT Will Support Energy Management in Smart Factory
5.10 IoT Energy Management Architecture for Industrial Applications
5.10.1 IoT-Based Energy Management Technology
5.10.2 Energy Harvesting
5.11 Case Study: Smart Factory
5.11.1 Supply Side
5.11.2 Photovoltaic Power Generation
5.11.3 Smart Micro-Grid
5.11.4 Demand Side
5.11.5 Virtualization
5.12 Conclusion
References
6. IOT-Based Advanced Energy Management in Smart Factories
M. Nalini, Dhanashree Varadharajan, Nithyashree Natarajan and Yogabhuvaneswari Umasankar
6.1 Introduction
6.2 Smart Factory Benefits of IOT-Based Advanced Energy Management
6.3 Role of IOT Technology in Energy Management
6.4 Developing an IOT Information Model for Energy Efficiency
6.5 Integrating Intelligent Energy Systems (IES) and Demand Response (DR)
6.6 How to Accurately Measure and Manage Your Energy Usage
6.7 Introduction to Energy Efficiency Measures
6.8 Identifying Opportunities to Reduce Energy Use
6.9 Monitoring and Measuring Energy Usage
6.10 Establishing Accounting and Incentives
6.11 Sustaining the Long-Term Benefits of Optimized Energy Usage
6.12 Role of Cyber Security When Implementing IoT-Based Advanced Energy Solutions
6.13 Materials Required in Smart Factories
6.14 Methods in IoT-Based Smart Factory Implementation
6.15 Steps for Developing an IoT-Based Energy Management System
6.15.1 Assess Current Energy Usage
6.15.2 Develop an Energy Conservation Plan
6.15.3 Implement IoT Technology
6.15.4 Monitor Results
6.16 Challenges For Adopting IoT-Based Energy Management Systems
6.16.1 Big Data and Analytics
6.16.2 Connectivity Constraints
6.16.3 Data Security and Privacy Issues
6.16.4 Device Troubleshooting
6.17 Recommendations for Overcoming the Challenges With Implementing IoT-Based Advanced Energy Solution
6.17.1 IoT-Enabled Automation
6.17.2 Smart Sensors
6.17.3 Predictive Analytics
6.18 Case Studies
6.18.1 Automated Demand Response (ADR)
6.18.2 Automated Maintenance
6.18.3 Predictive Analytics
6.19 Case Studies for Successful Implementation
6.20 Applications
6.21 Different Techniques for Monitoring and Control of IoT Devices
6.22 Literature Survey
6.23 Conclusion
References
7. Challenges in Ensuring Security for Smart Energy Management Systems Based on CPS
V. M. Meera and K. P. Arjun
7.1 Introduction
7.1.1 Brief Overview of Smart Energy Management Systems and Cyber-Physical Systems
7.1.2 Importance of Security in CPS-Based Smart Energy Management
7.2 Cyber-Physical Systems and Smart Energy Management
7.2.1 CPS Architecture and Components
7.2.2 Types of CPS-Based Smart Energy Management Systems
7.2.3 Common Communication Protocols Used in CPS-Based Smart Energy Management
7.2.4 Cyber Security Threats in CPS-Based Systems
7.3 Security Challenges in CPS-Based Smart Energy Management
7.3.1 Cyber Security Threats to CPS-Based Smart Energy Management Systems
7.3.2 Vulnerabilities of Communication Protocols Used in Smart Energy Management
7.3.3 Attack Vectors for Compromising CPS-Based Smart Energy Management Systems
7.4 Cyber Security Standards and Guidelines for Smart Energy Management
7.4.1 Cyber Security Incidents in Smart Energy Management
7.5 Conclusion
References
8. Security Challenges in CPS-Based Smart Energy Management
Lucia Agnes Beena T., Vinolyn Vijaykumar and Mercy P.
8.1 Introduction
8.2 CPS Architecture
8.3 The Driving Forces for CPS
8.3.1 Big Data
8.3.2 Cloud
8.3.3 Machine-to-Machine Communication and Wireless Sensor Networks
8.3.4 Mechatronics
8.3.5 Cybernetics
8.3.6 Systems of Systems
8.4 Advances in Cyber-Physical Systems
8.4.1 Application Domains of CPS
8.4.1.1 Industrial Transformation
8.4.1.2 Smart Grid
8.4.1.3 Healthcare
8.4.1.4 Smart Parking System
8.4.1.5 Household CPS
8.4.1.6 Aerospace
8.4.1.7 Agriculture
8.4.1.8 Construction
8.5 Energy Management through CPS
8.5.1 Energy Management of CPS for Smart Grid
8.5.2 Energy Management of CPS for Smart Building Structure
8.5.3 Energy Management of CPS for Autonomous Electric Vehicles in Smart Transportation
8.5.4 Energy Management of CPS for Smart Industry
8.5.5 Energy Management of CPS for Home Automation
8.6 Security Issues in CPS
8.6.1 Threats
8.6.1.1 Cyber Threats
8.6.1.2 Physical Threats
8.6.2 CPS Vulnerabilities
8.6.3 CPS Attacks
8.6.4 CPS Failures
8.6.5 Risk Identification and Management
8.6.6 Protecting CPS
8.6.7 Security Solutions for CPS
8.7 Open Challenges and Future Directions
8.7.1 Open Challenges
8.7.1.1 Infrastructure Challenges
8.7.1.2 Network Communication Challenges
8.7.1.3 Control Operational and Computational Challenges
8.7.1.4 CPS Deployment Challenges
8.7.2 Future Directions
8.8 Conclusion
References
9. Blockchain-Based Energy Transmission System: Design, Optimization, and Data-Driven Modeling
Prabha Selvaraj, Rohit Kumar Das, Vijay Kumar Burugari, Ganesh Reddy Karri, Kanmani P. and Anupama Namburu
9.1 Introduction
9.2 Literature Review
9.2.1 Essential Parts of a Blockchain Include
9.2.2 Blockchain and Smart Agreements
9.2.2.1 Blockchain 3.0 Scalability and Interoperability
9.2.2.2 Interoperability
9.2.2.3 Blockchain 4.0 Scalability
9.2.2.4 Energy Efficiency
9.2.2.5 Possible Solutions
9.3 Case Study and Application
9.3.1 Energy Transmission Monitoring with Advanced Metering Infrastructure
9.3.2 Energy Optimization with Home Automation
9.3.3 Renewable Microgrids
9.3.4 Blockchain for Electric Vehicles
9.4 Conclusion
References
10. Explainable AI Technology in E-CPS: Policy Design, Economic Research, and Case Studies
Thangaraja Arumugam, Saritha Bantu, Yeligeti Raju, Renuka Deshmukh and B. Raja Mannar
10.1 Introduction
10.1.1 Terminology
Nomenclature
10.2 E-CPS Arrangement
10.2.1 E-CPS Framework
10.3 Case Study: Method Depiction
10.3.1 Fixing Constraints
10.3.2 Information Preparation
10.3.3 Prediction Framework
10.3.4 Controlling Approach
10.3.5 Result Analysis
10.3.6 Overview
10.4 Transformation of the Power Infrastructure
10.4.1 Cyber-Physical System
10.4.2 Power Effectiveness—Cumulative Power Efficacy
10.5 Power Managing Structures
10.5.1 Following that are Some Notable Instances of How CPS Affects Power Sources
10.5.2 Data Analysis
10.5.3 Utilising Agent-Based Modelling and Linear Optimization for Improved Urban Planning
10.5.4 Enhancing Compatibility and Utilization of e-CPS Components for Improved Administration of Commercial Structures
10.5.5 e-CPS Effects on the Power Change
10.5.6 Policies Involved and Economics Research
10.6 Protection Policies
10.7 Urgent Need for Effective Governance of AI and e-CPS
10.8 Conclusions
References
11. Infrastructural Data Visualization and Improved User Interfaces of Energy Consumption in Smart Cities
Prabha Selvaraj, Kanmani P., T.Y.J. Naga Malleswari, Vijay Kumar Burugari and S. Sudheer Mangalampalli
11.1 Introduction
11.1.1 Internet of Things (IoT)
11.1.2 Big Data
11.1.3 Cloud Computing
11.1.3.1 Infrastructure in Smart City
11.1.3.2 Types of Smart Infrastructure
11.1.4 Issues with Smart City Infrastructure
11.1.4.1 Organizational Issues
11.1.4.2 Data Quality and Collection Issues
11.1.4.3 Governance and Privacy Issues
11.1.4.4 Maintenance and Durability
11.2 Literature Review
11.3 Visualization Tools and Interfaces Used in Smart Cities Using IoT
11.4 Energy Representation Frameworks
11.5 Materials and Methods
11.5.1 Smart Cities and Energy Consumption
11.5.1.1 Active Approach
11.5.1.2 Passive Approach
11.5.2 Importance of Energy-Efficient in Sustainable Buildings
11.5.3 Energy Consumption and Management in Smart Cities
11.5.4 Materials and Strategies
11.5.4.1 Requirements and Work Processes
11.5.4.2 Data Collection
11.5.5 Visual Encoding and Communication Plan
11.5.5.1 Map and Local Area Wayfarer
11.5.5.2 Scatterplot and Examination Diagram
11.6 Case Study and Applications
11.6.1 Functionalities of the Energy Hub Platform
11.6.1.1 Mechanisms of the Energy Conservation for Smart Cities
11.6.1.2 Smart Electricity Grids for Smart Cities
11.6.1.3 Data Visualization and Its Importance in Smart Cities
11.6.1.4 Security Challenges in Smart City
11.6.1.5 Smart Transportation and Smart Traffic Management
11.6.1.6 Domestic Renewable Energy System Integration in Cities
11.7 Factors for the Improvement of Energy Efficacy in Smart Cities
11.7.1 Prediction of Electrical Consumption in Smart Cities
11.8 Conclusion and Future Scope
References
12. Power Management in Intelligent Buildings Based on Daily Demand Prediction
V. Geethapriya, D. Sivamani, D. Shyam, A. Sangari, M. Manish, Prasheetha and Divina Julia
12.1 Introduction
12.1.1 Summary from Introduction
12.2 The Power Management System Block Diagram
12.3 Working Task of Power Management System
12.4 Simulation Model of Power Management System
12.5 Hardware Implementation of Power Management System
12.6 Safety Precautions in Smart Building Implementation
12.7 Conclusion
References
13. Schemes and Security Attacks on the Integrity of Cyber-Physical Systems in Energy Systems
Rajesh Kumar, Charanjeet Singh, Yeligeti Raju, Pratap Patil and K. Saravanan
13.1 Introduction
13.1.1 CPS Protection Purposes
13.1.2 Confidentiality
13.1.3 Authenticity
13.1.4 Accessibility
13.1.5 Resilience
13.1.6 Trustworthiness
13.2 CPS Safety Methodologies
13.2.1 Threat Categorisation
13.2.2 Spying
13.2.3 Sneaky Deceit Assault
13.2.4 Attack Using a Vulnerable Key
13.2.5 Assault on the Centre Spy
13.2.6 Jamming Assault
13.2.7 Replay Attack
13.2.8 Refusal of Package Assault
13.2.9 Assault Demonstrating
13.2.10 Assault Sensing
13.2.11 Safety Resolutions
13.2.12 Construction and Designing for Protection
13.2.13 Safety in Definite CPS
13.2.14 Energy System Safety
13.2.15 Medicinal CPS Safety
13.2.16 Portable CPS Safety
13.2.17 Motorised CPS Safety
13.3 Shielding in Contradiction of Information Safety Assaults
13.3.1 Enhancing Data Security in the Electricity System Through a Markov Decision Process (MDP)
13.3.2 Evaluating the Effectiveness of a Determination Method for Data Security Assaults in Power Systems
13.4 Scheme Variants
13.4.1 Assault Variant
13.5 Supervised Learning in Depth
13.5.1 DQND Scheme
13.5.2 Assault Situations
13.5.3 Markov Resolution Concepts
13.5.4 Assessment Spatial and Sliding Windows Measurements
13.5.5 DQND Scheme
13.5.6 System Education
13.5.7 Efficiency Assessment
13.5.8 Algorithm 1: Education Phase of DQND
13.5.9 Algorithm 2: Evaluation Phase of DQND
13.5.10 Assessment Metrics
13.5.11 Standards
13.6 Discussion
13.7 Conclusion
References
14. Adaptive Power System Resource Management in Cyber-Physical Energy Systems
Virendra Singh Kushwah, Indra Singh Bisht, Charanjeet Singh, K. Gurnadha Gupta and K. Suresh
14.1 Introduction
14.1.1 Modelling and Simulation of CPES for Integrating Data Networks with Electricity Networks
14.1.2 Actual-Period Energy Network Modelling and Simulation using RTLAB and OPNET Modeller with SITL Integration
14.1.3 Cyber Attack on Ukraine’s Power Grid in 2015: Incident Overview and Implications for Critical Infrastructure Security
14.1.4 CPES Sensitivity Evaluation Process Utilising Virtualized CP Linkages
14.2 CPES Structures
14.2.1 Diversified
14.2.2 Self Determination
14.2.3 Actual Period
14.2.4 Reconstitute
14.2.5 Consistency
14.2.6 Intensely Encapsulated
14.3 Development of CPES Structures
14.3.1 Assistances of Cyber-Physical Energy System
14.3.2 CPES Difficulties
14.3.3 CPES Forming
14.3.4 Computer Estimation of the Variability of the Network
14.4 Resource Management in Socio-CPS
14.5 Associated Study
14.5.1 Assessment of CP Multilateral Implications
14.6 The Integrated Modelling Platform for the CPES
14.6.1 Nodal Junction
14.6.2 PP Linkages
14.6.3 Nodal Junctions
14.6.4 CP Linkage
14.7 Assault from Without and Compounding Collapse
14.7.1 Procedure for Appropriate Load Diminishment
14.8 The Combination of Assault and Defence
14.8.1 Issues with Bi-Level Computing
14.8.2 Defence of Resource Allocation
14.8.3 Methodology for Security Testing
14.9 Case Studies
14.10 Conclusions and Future Work
References
15. Cyber-Physical Energy Systems for Electric Vehicles
ShaikMahaboob Basha, Akilandeswari P., Suguna M., Prakash D., Biruntha S. and Vivekanandan P.
15.1 Introduction
15.1.1 Smart-Use CPESs of Emerging Technologies for Sustainable Energy Solutions
15.1.2 Technology for Power Storage and Fuel Cells for CPES in EVS
15.1.3 Vehicle Cyber-Physical Energy Systems: Problems and Implications
15.1.4 Electric Drive-Train
15.1.5 Managing Storage Units (Batteries)
15.1.6 Dispersed Managing Batteries
15.2 Suggested Type
15.2.1 Activity Tracking Technique Deployment in CPES Using Electro-Mechanical Connections
15.2.2 MPSSU uses Ultra-Capacitors for Higher Energy Distribution and Rapid Power Outages
15.3 Outcomes from Experiments and Simulations
15.3.1 Modeling the DC Bus Network for SCPEDS Using the Port-Hamiltonian Approach
15.3.2 Electric Vehicle Energy Conversion and Inversion Simulation using the PSIM Program
15.3.3 Additional Energy Management Techniques Explored in Studies
15.4 Discussion
15.4.1 Power-Controlling and Autonomous Vehicle Diagnosis Using Genetic Algorithms (GAs)
15.5 Conclusion
References
16. Design and Implementation of IoT‑Based Advanced Energy Management System for Smart Factory
S. Jayanthi, N. Suresh Kumar, Zafar Ali Khan N., S. Sreenatha Reddy, R. Santhosh and Pachipala Yellamma
16.1 Introduction
16.1.1 Driving Factors
16.1.2 Industry 5.0
16.1.3 Smart Metres
16.2 Challenges Faced by Factories Today
16.2.1 How Do Businesses Try to Get Over the Obstacles That Exist in Their Manufacturing Plants?
16.2.2 Prospects of Industrial IoT
16.2.3 Impact of IoT on Smart Factories
16.3 Home Energy Management Systems (HEMSs)
16.4 Micro Grid for Integration of Several Sources and Storage
16.4.1 Deming Cycle
16.4.2 Setbacks of Effective Smart Energy Systems
16.4.3 Essential Sensing Technologies in Smart Factories
16.4.4 Four Cognitive Facets Define a Smart Factory
16.4.5 Reasons Why Industries Need to Fully Utilise IoT’s Benefits
16.5 Proposed Robust Energy Management System for Smart Factories
16.6 Conclusion
16.7 Future Trends
References
Index
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