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A Review of anomaly detection techniques in advanced metering infrastructure

Abbas M. Al-Ghaili, Zul- Azri Ibrahim, Syazwani Arissa Shah Hairi, Fiza Abdul Rahim, Hasventhran Baskaran, Noor Afiza Mohd Ariffin, Hairoladenan Kasim
2021 Bulletin of Electrical Engineering and Informatics  
The purpose of this study is to review existing studies on anomalies techniques used to detect data manipulation in AMI and smart grid systems.  ...  Anomalies detection is a technique can be used to identify any rare event such as data manipulation that happens in AMI based on the data collected from the smart meter.  ...  ACKNOWLEDGMENT The  ... 
doi:10.11591/eei.v10i1.2026 fatcat:tc7cp5t4rva65jrelqbzjnqnmu

PowerNet: a smart energy forecasting architecture based on neural networks

Yao Cheng, Chang Xu, Daisuke Mashima, Partha P. Biswas, Geetanjali Chipurupalli, Bin Zhou, Yongdong Wu
2020 IET Smart Cities  
Finally, we briefly discuss a multi-layer anomaly/ electricity-theft detection approach based on PowerNet demand forecasting.  ...  Electricity demand forecasting is a critical task for efficient, reliable and economical operation of the power grid, which is one of the most essential building blocks of smart cities.  ...  Another stem of related work is the anomaly detection in smart grids for non-technical loss such as electricity theft. Bandim et al.  ... 
doi:10.1049/iet-smc.2020.0003 fatcat:u7wo6jl5u5djrncx6nkphar5im

Understanding the role of buildings in a smart microgrid

Y Agarwal, T Weng, R K Gupta
2011 2011 Design, Automation & Test in Europe  
In this paper, we examine the significant role that buildings play in energy use and its management in a smart microgrid.  ...  At the scale of a small town, a microgrid is connected to the wide-area electrical grid that may be used for 'baseline' energy supply; or in the extreme case only as a storage system in a completely self-sufficient  ...  Connected to the smart grid, these microgrids allow for better accounting of energy as it flows between the two grids, and for increased resilience to anomalies.  ... 
doi:10.1109/date.2011.5763195 dblp:conf/date/AgarwalWG11 fatcat:2rjrmaj4kzd3hcpd4kwfj2cdlm

Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review

Eklas Hossain, Imtiaj Khan, Fuad Un-Noor, Sarder Shazali Sikander, Md. Samiul Haque Sunny
2019 IEEE Access  
This paper conducts a comprehensive study on the application of big data and machine learning in the electrical power grid introduced through the emergence of the next-generation power system-the smart  ...  grid (SG).  ...  to find out the optimum timeframe and technological approach to move towards the smart grid architecture. • The challenges in transitioning to the renewable energy-centric smart grid, and their feasible  ... 
doi:10.1109/access.2019.2894819 fatcat:2525icn33resjpigdjk45svyq4

PowerNet: Neural Power Demand Forecasting in Smart Grid [article]

Yao Cheng, Chang Xu, Daisuke Mashima, Vrizlynn L. L. Thing, Yongdong Wu
2019 arXiv   pre-print
Finally, we briefly discuss a multilayer anomaly detection approach based on PowerNet.  ...  Power demand forecasting is a critical task for achieving efficiency and reliability in power grid operation.  ...  ACKNOWLEDGEMENT This research is supported by the National Research Foundation, Prime Minister's Office, Singapore under the Energy Programme and administrated by the Energy Market Authority (EP Award  ... 
arXiv:1904.11979v1 fatcat:fwcp47yo3ndo7f7ff7c5bci64y

On Stability, Ancillary Services, Operation, and Security of Smart Inverters [article]

Tareq Hossen, Fahmid Sadeque
2021 arXiv   pre-print
Moreover, the power grid is moving toward becoming a cyber-physical system in which smart inverters can exchange information for power marketing and economic dispatching.  ...  A grid-interactive inverter performs as a controllable interface between the distributed energy sources and the power grid.  ...  Therefore, a self-security algorithm can ensure a secure operation by detecting anomalies in the incoming data.  ... 
arXiv:2112.06787v1 fatcat:cquvnriyyrbj3eyq3eg7k7ehie

Micro Smart Micro-grid and Its Cyber Security Aspects in a Port Infrastructure

Monica Canepa, Giampaolo Frugone, Riccardo Bozzo, Stefan Schauer
2020 American Journal of Information Science and Technology  
Current technology allows the deployment of a local micro-grid of the size of tenths of MW, capable of islanded operation in case of emergency and to grant an increasing energy independency.  ...  Unfortunately the smart grid is a critical asset within the port infrastructure and its intelligence is a high-level target for cyberattacks.  ...  Recognition of anomalies inside the "big" data characterizing the grid (outlier detection, SVM, anomaly detection, etc.).  ... 
doi:10.11648/j.ajist.20200401.11 fatcat:rswp2rdiz5hfpfas3ckvgxjs3e

Detecting Malicious Signal Manipulation in Smart Grids Using Intelligent Analysis of Contextual Data

Farzan Majdani, Lynne Batik, Andrei Petrovski, Sergei Petrovski
2020 13th International Conference on Security of Information and Networks  
In the present study we suggested an approach to effective detection of operational anomalies in Smart Grid systems based on machine learning algorithms that are capable of processing both substation sensor  ...  Intrusion Detection Systems for Smart Grid Efforts to make the new Smart Grids more secure have been underway at every stage of Smart Grid development, but for the purposes of this research we are focusing  ... 
doi:10.1145/3433174.3433613 fatcat:wpjnuj2xabgpbhk64jn4llhqb4

Behavior-Rule Based Intrusion Detection Systems for Safety Critical Smart Grid Applications

Robert Mitchell, Ing-Ray Chen
2013 IEEE Transactions on Smart Grid  
(SEMs) of a modern electrical grid in which continuity of operation is of the utmost importance.  ...  In this paper, a behavior-rule based intrusion detection system (BRIDS) is proposed for securing head-ends (HEs), distribution access points/data aggregation points (DAPs) and subscriber energy meters  ...  INTRODUCTION T HE most prominent characteristic of a smart grid such as a modern electrical grid or electricity infrastructure is the feedback loop that acts on the physical environment.  ... 
doi:10.1109/tsg.2013.2258948 fatcat:4njcgzn7ybhyff5oq6ga43hvdm

Special Issue on Cyber-Physical Systems (CPS)—Part I

Song Guo, Hannes Frey, Nei Kato, Yunhao Liu
2013 IEEE Transactions on Emerging Topics in Computing  
in the smart grid.  ...  The paper ''A Game-Theoretical Scheme in the Smart Grid With Demand-Side Management: Towards a Smart Cyber-Physical Power Infrastructure'' by Shengrong Bu and F.  ... 
doi:10.1109/tetc.2013.2276731 fatcat:lhoh645hsfetnb43zxd74tdfoq

Towards Big Data Electricity Theft Detection Based on Improved RUSBoost Classifiers in Smart Grid

Rehan Akram, Nasir Ayub, Imran Khan, Fahad R. Albogamy, Gul Rukh, Sheraz Khan, Muhammad Shiraz, Kashif Rizwan
2021 Energies  
The electric power produced by different sources is distributed to consumers by the transmission line and grid stations.  ...  The advent of the new millennium, with the promises of the digital age and space technology, favors humankind in every perspective.  ...  Conflicts of Interest: The authors declare no conflict of interest. Energies 2021, 14, 8029  ... 
doi:10.3390/en14238029 fatcat:oe6vfrjdeze2loq3jupdnsybla

Intrusion Resilience for PV Inverters in a Distribution Grid Use-Case Featuring Dynamic Voltage Control [chapter]

BooJoong Kang, David Umsonst, Mario Faschang, Christian Seitl, Ivo Friedberg, Friederich Kupzog, Henrik Sandberg, Kieran McLaughlin
2019 Lecture Notes in Computer Science  
ICT-enabled smart grid devices, potentially introduce new cyber vulnerabilities that weaken the resilience of the electric grid.  ...  An automated resilience mechanism is therefore presented, combining intrusion detection and decentralised resilient controllers, which is demonstrated to assure stable operation of an energy system by  ...  The global centre can identify inconsistencies by applying stateful analysis and anomaly detection on the global view of the network.  ... 
doi:10.1007/978-3-030-37670-3_8 fatcat:5hirydzq5nfo7crsmdp5ooqzay

Signature-Based Method and Stream Data Mining Technique Performance Evaluation for Security and Intrusion Detection in Advanced Metering Infrastructures (AMI)

Ziaeddin Najafian, Vahe Aghazarian, Alireza Hedayati
2015 International Journal of Computer and Electrical Engineering  
Smart grid applications pose a number of research challenges and of the most important challenge in Smart grid is security and privacy issues in smart metering [1]; Power smart girds  ...  The most important operation of AMI is creating a two-sided connection in order to collect, evaluate and analyze data about usage of energy by helping the dynamic power market installation, energy power  ...  Acknowledgment This research was sponsored by PaudRaad Industrial Group and Advanced Metering Infrastructure R&D unit of Paya Energy Company.  ... 
doi:10.17706/ijcee.2015.v7.879 fatcat:7nghui5u5vadppf4kc5vhsvzqq

Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures

Nikos Komninos, Eleni Philippou, Andreas Pitsillides
2014 IEEE Communications Surveys and Tutorials  
The threats detected are categorized according to specific security goals set for the Smart Home/Smart Grid environment and their impact on the overall system security is evaluated.  ...  This paper focuses on issues related to the security of the Smart Grid and the Smart Home, which we present as an integral part of the Smart Grid.  ...  The integration of the Energy Aware Smart Home to the Smart Grid assuredly leads towards the successful meeting of some of the Smart Grid's major goals.  ... 
doi:10.1109/comst.2014.2320093 fatcat:46nkbgpqqndxhk2uetyddviwz4

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Yi Wang, Qixin Chen, Tao Hong, Chongqing Kang
2018 IEEE Transactions on Smart Grid  
How to employ massive smart meter data to promote and enhance the efficiency and sustainability of the power grid is a pressing issue.  ...  In addition, we also discuss some research trends, such as big data issues, novel machine learning technologies, new business models, the transition of energy systems, and data privacy and security.  ...  The works on anomaly detection in smart meter data are summarized from the perspective of bad data detection and NTL detection (or energy theft detection).  ... 
doi:10.1109/tsg.2018.2818167 fatcat:yacc5fol6vhydkw2azgy4mpfai
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