The suggested framework of this work opens the door for creative solutions that support a more resilient and sustainable
energy infrastructure in addition to enhancing the capabilities of currently available Smart Grid applications.
Smart Grid integrates renewable and green technology into the traditional electrical infrastructure. Smart embedded gadgets with sophisticated decision-making capabilities will boost Smart Grid's efficiency. Energy industry has seen a transformation because of the incorporation of Internet of Things technology in Smart Grids. Edge Computing is applied to enhance efficiency and reliability of Smart Grid operations. A complete ecosystem for smart cities is created when digital platforms, edge computing, and IoT solutions are combined. They make it possible for massive amounts of data to be gathered, processed, and analysed, enabling city officials, businesses, and citizens to make wise decisions and promote innovation. In conclusion, a convincing paradigm for addressing the changing issues in the energy industry is presented by the combination of IoT and Edge Computing in Smart Grids.
Table of Contents
1. INTRODUCTION
1.1 Overview of Internet of Things (IoT)
1.2 Overview of Smart Grid
1.3 Overview of Edge Computing (EC)
2. Smart Grid
2.1 Smart Grid Essentials:
3. Understanding IoT in Smart Grids
3.1 Applications
3.1.1 IoT in Power Generation
3.1.2 IoT in Transmission
3.1.3 IoT in Substation
3.1.4 IoT in Distribution, Utilization, and Dispatch
3.1.5 IoT in Smart Metering
4. Introduction to Edge Computing
4.1 Edge computing and its fundamental principles
4.2 Important Features of Edge Computing [43]:
4.3. Benefits of Edge Computing [15]
5. Integration of EC in Smart Grids
5.1 Edge computing's contribution to improving IoT device capabilities in smart grids
5.2 How edge computing allows real-time data processing, analysis, and decision-making at the network edge?
6. Challenges and Open Issues
6.1 Scalability and Reliability
6.2. Sustainability
6.3 Flexibility
6.4 Security and Privacy
7. Future Directions and Conclusion
Research Objectives and Key Topics
The primary aim of this work is to investigate the synergistic integration of Internet of Things (IoT) technology and Edge Computing (EC) within modern Smart Grid infrastructures to resolve critical bottlenecks regarding latency, data management, and operational efficiency in energy distribution and monitoring systems.
- Integration of IoT-enabled intelligent sensors in electrical power systems.
- Architectural shifts from centralized cloud computing to distributed edge nodes.
- Real-time data processing strategies for enhanced grid stability and situational awareness.
- Addressing scalability, security, privacy, and sustainability challenges in next-generation grids.
Excerpt from the Book
3. Understanding IoT in Smart Grids
IoT technology is becoming more and more important. IoT refers to a networked device that can communicate and share data, which can then be analyze by people on a computer. Billions of smart devices are integrated into complex networks to provide dynamic functionality such as keeping an eye on and overseeing vital communications and infrastructure [26]. Three key concepts underpin the Internet of Things: things, semantics, and the internet. Things-oriented ideas make use of a variety of smart devices, including cameras, laser scanners, sensors, actuators, RFID tags, and GPS. The internet-oriented idea facilitates connectivity among smart devices using various communication technologies such as Zig Bee, Bluetooth and WiFi. The semantic-oriented notion encompasses several applications with the help of intelligent gadgets. The IoT links many networked gadgets used in everyday life to the Internet. Multiple sectors such as healthcare, transportation, security surveillance, agriculture, power grids, household appliances, and military have been automated using IoT technology [27]. Literature studies have extensively covered several aspects of IoT, including architectural features, permissive technologies, implementation, and open issues [28-30]. Studies on the IoT's wireless networks for communication can be located in the references. [31-36]. Standard devices with transceivers, protocol stacks, and microcontrollers are known as Internet of Things objects.
Chapter Summaries
1. INTRODUCTION: Provides a foundational overview of IoT, Smart Grid concepts, and the transition toward Edge Computing to solve cloud-related latency issues.
2. Smart Grid: Explores the essential features and objectives of modern Smart Grids, including advanced metering and automatic grid monitoring.
3. Understanding IoT in Smart Grids: Analyzes the conceptual framework of IoT in energy systems and its specific applications across power generation, transmission, and distribution.
4. Introduction to Edge Computing: Discusses the fundamental principles, features, and advantages of deploying Edge Computing instead of traditional centralized data centers.
5. Integration of EC in Smart Grids: Examines how Edge Computing enhances IoT capabilities for real-time analysis and decision-making at the network edge.
6. Challenges and Open Issues: Addresses the persistent technical hurdles, including security, privacy, scalability, and sustainability concerns in decentralized grid environments.
7. Future Directions and Conclusion: Summarizes the study’s findings and outlines the strategic role of edge-based architectures in achieving efficient, reliable future energy networks.
Keywords
Internet of Things, IoT, Smart Grid, Edge Computing, Power Distribution, Data Latency, Renewable Energy, Network Architecture, Real-time Analysis, Cybersecurity, Resource Provisioning, Sustainability, Scalability, Digital Twin, Smart Metering.
Frequently Asked Questions
What is the core focus of this publication?
The publication focuses on the convergence of IoT and Edge Computing technologies to optimize the management, efficiency, and real-time responsiveness of modern Smart Grid energy systems.
Which primary technological domains are examined?
The main domains are Internet of Things (IoT), Edge Computing, Smart Grid infrastructure, and data management frameworks for electrical utility systems.
What is the central research objective defined?
The goal is to analyze how localized (edge) processing can overcome the limitations of distance and latency found in traditional cloud-based centralized systems.
What methodologies are addressed in the book?
The work covers architectural frameworks for decentralized monitoring, load balancing algorithms, resource allocation strategies, and digital twin simulation approaches.
What key aspects are discussed in the main chapters?
The chapters cover a progression from basics of IoT and Smart Grids, through the implementation of Edge Computing, to a detailed assessment of operational challenges and future scalability.
Which terms best characterize this work?
Relevant terms include "Edge Computing," "Smart Grid," "IoT Integration," "Latency Reduction," and "Grid Security."
How does Edge Computing differ from standard Cloud Computing in this context?
Edge Computing brings processing closer to the data source (near the user or substation), whereas Cloud Computing relies on centralized, distant servers that introduce higher latency.
What role does crowd-sensing play in the proposed frameworks?
Crowd-sensing enables a wider, dynamic collection of data from distributed smart devices, turning them into "data workers" to enhance the grid's precision.
Why are security and privacy highlighted as significant issues?
Because the expansion of IoT devices and decentralized nodes increases potential vulnerabilities, making robust encryption and authentication on the edge essential for safety.
- Quote paper
- Brinda Patel (Author), Jigar Sarda (Author), Amit Thakkar (Author), Arpita Patel (Author), 2024, IoT Applications in Smart Grids Using Edge Computing, Munich, GRIN Verlag, https://www.grin.com/document/1499929
