Survey of Big Data Role in Smart Grids: Definitions, Applications, Challenges, and Solutions

2018 ◽  
Vol 12 (1) ◽  
pp. 86-97 ◽  
Author(s):  
Mahmoud Ghofrani ◽  
Andrew Steeble ◽  
Christopher Barrett ◽  
Iman Daneshnia
Keyword(s):  
Big Data ◽  
Smart Grid ◽  
Smart Grids ◽  
Power Grids ◽  
Time Data ◽  
Smart Meters ◽  
Communication Devices ◽  
Big Data Technologies ◽  
Big Data Application ◽  
Real Time Data Processing

Objective:This paper provides a literature review on smart grids and big data. Smart grid refers to technologies used to modernize the energy delivery of traditional power grids, using intelligent devices and big data technologies.Methods:The modernization is performed by deploying equipment such as sensors, smart meters, and communication devices, and by invoking procedures such as real-time data processing and big data analysis. A large volume of data with high velocity and diverse variety are generated in a smart grid environment.Conclusion:This paper presents definitions and background of smart grid and big data. Current studies and research developments of big data application in smart grids are also introduced. Additionally, big data challenges in smart grid systems such as security and data quality are discussed.

IoT Big Data Security, Privacy and Challenges Related to Smart Grid

2022 ◽  
pp. 368-379
Author(s):  
Kimmi Kumari ◽  
M. Mrunalini
Keyword(s):  
Big Data ◽  
Smart Grid ◽  
Smart Grids ◽  
Type Systems ◽  
Heterogeneous Data ◽  
Security Measures ◽  
Smart Meters ◽  
Efficient Manner ◽  
Security Issues ◽  
Iot Devices

The highly interconnected network of heterogeneous devices which enables all kinds of communications to take place in an efficient manner is referred to as “IOT.” In the current situation, the data are increasing day by day in size as well as in terms of complexities. These are the big data which are in huge demand in the industrial sectors. Various IT sectors are adopting big data present on IOT for the growth of their companies and fulfilling their requirements. But organizations are facing a lot of security issues and challenges while protecting their confidential data. IOT type systems require security while communications which is required currently by configuration levels of security algorithms, but these algorithms give more priority to functionalities of the applications over security. Smart grids have become one of the major subjects of discussions when the demands for IOT devices increases. The requirements arise related to the generation and transmission of electricity, consumption of electricity being monitored, etc. The system which is responsible to collect heterogeneous data are a complicated structure and some of its major subsystems which they require for smooth communications include log servers, smart meters, appliances which are intelligent, different sensors chosen based on their requirements, actuators with proper and efficient infrastructure. Security measures like collection, storage, manipulations and a massive amount of data retention are required as the system is highly diverse in its architecture and even the heterogeneous IOT devices are interacting with each other. In this article, security challenges and concerns of IOT big data associated with smart grid are discussed along with the new security enhancements for identification and authentications of things in IOT big data environments.

scholarly journals Generation of dynamic energy management using data mining techniques basing on big data analytics isssues in smart grids

2018 ◽  
Vol 7 (2.26) ◽  
pp. 85
Author(s):  
Dr E. Laxmi Lydia ◽  
B Prasanna Kumar ◽  
D Ramya
Keyword(s):  
Big Data ◽  
Smart Grid ◽  
Data Processing ◽  
Energy Management ◽  
Electricity Market ◽  
Smart Grids ◽  
Data Analytics ◽  
Performance Estimation ◽  
Smart Meters ◽  
Dynamic Energy Management

The Optimal bidirectional flow of the electric power and the communicational data between suppliers and consumers are greatly enabled by the Smart Electricity in Grid. Reliable and Feasible micro energy generated due to Dynamic Energy Management (DEM) and the electricity market by consumers and suppliers. The smart grid features ICCM, aims to bring out the power at reduced cost. Powerful and practical DEM relies on load and sustainable production. Smart meters attain the huge data quantity through practical methods and solutions in this real world working. Smart Grids are enhanced by the operations such as data analytics, giving out high performance estimation, Adequate data network management and cloud computing. This paper aims focusthe issuesin big data and challenges experienced by the Dynamic Energy Management signed in Smart Grid. A detail explanation of data processing techniques that are mostly implemented and It also provides a brief description of the most commonly used data processing methods and recommended proposes a upcoming future directional research in thefield. 

Big Data Business Intelligence in Bank Risk Analysis

2015 ◽  
Vol 6 (2) ◽  
pp. 55-77 ◽  
Author(s):  
Nayem Rahman ◽  
Shane Iverson
Keyword(s):  
Big Data ◽  
Risk Analysis ◽  
Best Practices ◽  
Business Intelligence ◽  
Banking Industry ◽  
Bank Risk ◽  
Time Data ◽  
Real Time Data ◽  
Big Data Technologies ◽  
Real Time Data Processing

This paper provides an overview of big data technologies and best practices from the standpoint of business intelligence (BI) applications in the banking industry. The authors discussed current challenges in banking industry that could be addressed by using big data technologies. Based on their research, they provided a list of big data tools and technologies in terms of an ecosystem that are suitable for real-time data processing and capable in bank fraud detection and prevention, and other bank risk analysis. They highlighted how business intelligence could be leveraged with the help of emerging big data technologies.

IoT Big Data Security, Privacy and Challenges Related to Smart Grid

2019 ◽  
Vol 8 (2) ◽  
pp. 1-10
Author(s):  
Kimmi Kumari ◽  
M. Mrunalini
Keyword(s):  
Big Data ◽  
Smart Grid ◽  
Smart Grids ◽  
Type Systems ◽  
Heterogeneous Data ◽  
Security Measures ◽  
Smart Meters ◽  
Efficient Manner ◽  
Industrial Sectors ◽  
Iot Devices

The highly interconnected network of heterogeneous devices which enables all kinds of communications to take place in an efficient manner is referred to as “IOT.” In the current situation, the data are increasing day by day in size as well as in terms of complexities. These are the big data which are in huge demand in the industrial sectors. Various IT sectors are adopting big data present on IOT for the growth of their companies and fulfilling their requirements. But organizations are facing a lot of security issues and challenges while protecting their confidential data. IOT type systems require security while communications which is required currently by configuration levels of security algorithms, but these algorithms give more priority to functionalities of the applications over security. Smart grids have become one of the major subjects of discussions when the demands for IOT devices increases. The requirements arise related to the generation and transmission of electricity, consumption of electricity being monitored, etc. The system which is responsible to collect heterogeneous data are a complicated structure and some of its major subsystems which they require for smooth communications include log servers, smart meters, appliances which are intelligent, different sensors chosen based on their requirements, actuators with proper and efficient infrastructure. Security measures like collection, storage, manipulations and a massive amount of data retention are required as the system is highly diverse in its architecture and even the heterogeneous IOT devices are interacting with each other. In this article, security challenges and concerns of IOT big data associated with smart grid are discussed along with the new security enhancements for identification and authentications of things in IOT big data environments.

scholarly journals A Comprehensive Survey on Cyber-Physical Smart Grid Testbed Architectures: Requirements and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1043
Author(s):  
Abdallah A. Smadi ◽  
Babatunde Tobi Ajao ◽  
Brian K. Johnson ◽  
Hangtian Lei ◽  
Yacine Chakhchoukh ◽  
...  
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Smart Grids ◽  
Data Exchange ◽  
Information Technologies ◽  
New Technologies ◽  
Rapid Development ◽  
Environmental Benefits ◽  
Future Research ◽  
Time Data

The integration of improved control techniques with advanced information technologies enables the rapid development of smart grids. The necessity of having an efficient, reliable, and flexible communication infrastructure is achieved by enabling real-time data exchange between numerous intelligent and traditional electrical grid elements. The performance and efficiency of the power grid are enhanced with the incorporation of communication networks, intelligent automation, advanced sensors, and information technologies. Although smart grid technologies bring about valuable economic, social, and environmental benefits, testing the combination of heterogeneous and co-existing Cyber-Physical-Smart Grids (CP-SGs) with conventional technologies presents many challenges. The examination for both hardware and software components of the Smart Grid (SG) system is essential prior to the deployment in real-time systems. This can take place by developing a prototype to mimic the real operational circumstances with adequate configurations and precision. Therefore, it is essential to summarize state-of-the-art technologies of industrial control system testbeds and evaluate new technologies and vulnerabilities with the motivation of stimulating discoveries and designs. In this paper, a comprehensive review of the advancement of CP-SGs with their corresponding testbeds including diverse testing paradigms has been performed. In particular, we broadly discuss CP-SG testbed architectures along with the associated functions and main vulnerabilities. The testbed requirements, constraints, and applications are also discussed. Finally, the trends and future research directions are highlighted and specified.

Securing SDN-Enabled Smart Power Grids

2018 ◽  
pp. 79-98
Author(s):  
Uttam Ghosh ◽  
Pushpita Chatterjee ◽  
Sachin Shetty
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Single Point ◽  
Performance Comparison ◽  
Power Grids ◽  
Smart Power ◽  
Control Center ◽  
Grid Networks ◽  
Result Show ◽  
Sdn Controller

Software-defined networking (SDN) provides flexibility in controlling, managing, and dynamically reconfiguring the distributed heterogeneous smart grid networks. Considerably less attention has been received to provide security in SDN-enabled smart grids. Centralized SDN controller protects smart grid networks against outside attacks only. Furthermore, centralized SDN controller suffers from a single point of compromise and failure which is detrimental to security and reliability. This chapter presents a framework with multiple SDN controllers and security controllers that provides a secure and robust smart grid architecture. The proposed framework deploys a local IDS to provide security in a substation. Whereas a global IDS is deployed to provide security in control center and overall smart grid network, it further verifies the consequences of control-commands issued by SDN controller and SCADA master. Performance comparison and simulation result show that the proposed framework is efficient as compared to existing security frameworks for SDN-enabled smart grids.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

Formal Verification of ZigBee-Based Routing Protocol for Smart Grids

2021 ◽  
pp. 1002-1017
Author(s):  
Adnan Rashid ◽  
Osman Hasan
Keyword(s):  
Smart Grid ◽  
Formal Methods ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Smart Grids ◽  
Communication Technologies ◽  
Power Grids ◽  
Communication Link ◽  
Grid Systems ◽  
Efficiency Performance

Smart grids provide a digital upgradation of the conventional power grids by alleviating the power outages and voltage sags that occur due to their inefficient communication technologies and systems. They mainly tend to strengthen the efficiency, performance, and reliability of the traditional grids by establishing a trusted communication link between their different components through routing protocols. The conventional methods, i.e., the computer-based simulations and net testing, for analyzing these routing network protocols are error-prone and thus cannot be relied upon while analyzing the safety-critical smart grid systems. Formal methods can cater for the above-mentioned inaccuracies and thus can be very beneficial in analyzing communication protocols used in smart grids. In order to demonstrate the utilization and effectiveness of formal methods in analyzing smart grid routing protocols, we use the UPPAAL model checker to formally model the ZigBee-based routing protocol. We also verify some of its properties, such as, liveness, collision avoidance and deadlock freeness.

Vulnerabilities and Threats in Smart Grid Communication Networks

2021 ◽  
pp. 1508-1535
Author(s):  
Yona Lopes ◽  
Natalia Castro Fernandes ◽  
Tiago Bornia de Castro ◽  
Vitor dos Santos Farias ◽  
Julia Drummond Noce ◽  
...  
Keyword(s):  
Smart Grid ◽  
Communication Networks ◽  
Smart Grids ◽  
Electrical Network ◽  
Physical Security ◽  
Smart Meters ◽  
Interconnected System ◽  
Other Information ◽  
Data Volume ◽  
Active Attacks

Advances in smart grids and in communication networks allow the development of an interconnected system where information arising from different sources helps building a more reliable electrical network. Nevertheless, this interconnected system also brings new security threats. In the past, communication networks for electrical systems were restrained to closed and secure areas, which guaranteed network physical security. Due to the integration with smart meters, clouds, and other information sources, physical security to network access is no longer available, which may compromise the electrical system. Besides smart grids bring a huge growth in data volume, which must be managed. In order to achieve a successful smart grid deployment, robust network communication to provide automation among devices is necessary. Therefore, outages caused by passive or active attacks become a real threat. This chapter describes the main architecture flaws that make the system vulnerable to attacks for creating energy disruptions, stealing energy, and breaking privacy.

Securing SDN-Enabled Smart Power Grids

2022 ◽  
pp. 1028-1046
Author(s):  
Uttam Ghosh ◽  
Pushpita Chatterjee ◽  
Sachin Shetty
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Single Point ◽  
Performance Comparison ◽  
Power Grids ◽  
Smart Power ◽  
Control Center ◽  
Grid Networks ◽  
Result Show ◽  
Sdn Controller

Software-defined networking (SDN) provides flexibility in controlling, managing, and dynamically reconfiguring the distributed heterogeneous smart grid networks. Considerably less attention has been received to provide security in SDN-enabled smart grids. Centralized SDN controller protects smart grid networks against outside attacks only. Furthermore, centralized SDN controller suffers from a single point of compromise and failure which is detrimental to security and reliability. This chapter presents a framework with multiple SDN controllers and security controllers that provides a secure and robust smart grid architecture. The proposed framework deploys a local IDS to provide security in a substation. Whereas a global IDS is deployed to provide security in control center and overall smart grid network, it further verifies the consequences of control-commands issued by SDN controller and SCADA master. Performance comparison and simulation result show that the proposed framework is efficient as compared to existing security frameworks for SDN-enabled smart grids.

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