A Study on Electricity Theft Detection and Control in Smart Grid Systems

2020 ◽  
Author(s):  
Syeda Pealy ◽  
Mohammad Abdul Matin
Keyword(s):  
Smart Grid ◽  
Grid Systems ◽  
Electricity Theft ◽  
And Control

Real Time Modeling and Control of Smart Grid Systems

2012 ◽  
pp. 1-26 ◽  
Author(s):  
Anurag K. Srivastava ◽  
Ramon Zamora ◽  
Noel N. Schulz ◽  
Krishnanjan G. Ravikumar ◽  
Vinoth M. Mohan
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Modeling And Control ◽  
Grid Systems ◽  
Time Modeling ◽  
And Control

scholarly journals Retraction: An Efficient Power Theft Detection Using Mean-Shift Clustering and Deep Learning in Smart Grid (IOP Conf. Ser.: Mater. Sci. Eng. 983 012003)

2020 ◽  
Vol 983 (1) ◽  
pp. 012018
Keyword(s):  
Smart Grid ◽  
Smart Home ◽  
Learning Algorithm ◽  
Mean Shift ◽  
Grid Systems ◽  
Link Type ◽  
Electricity Theft ◽  
Mean Shift Clustering ◽  
Energy Theft ◽  
Efficient Power

This article has been retracted by IOP Publishing following an allegation that this article contains text overlap from multiple unreferenced sources [1, 2, 3]. IOP Publishing has investigated and agree the article constitutes plagiarism. IOP Publishing also expresses concern regarding a number of nonsensical phrases used in the article, which suggests the article may have been created at least partly by artificial intelligence or translation software. If the authors wish to contest this retraction they are advised to contact [email protected]. 1. Jeyaranjani J, Devaraj D, "Machine Learning Algorithm for Efficient Power Theft Detection using Smart Meter Data" in International Journal of Engineering & Technology, vol. 7.3, pp. 900-904, 2018, https://www.sciencepubco.com/index.php/ijet/article/view/19585 2. Aswini. R. and Keerthiha. V., "IoT Based Smart Energy Theft Detection and Monitoring System for Smart Home," 2020 International Conference on System, Computation, Automation and Networking (ICSCAN), 2020, pp. 1-6, https://ieeexplore.ieee.org/document/9262411 3. Hasan M, Toma RN, Nahid AA, Islam MM and Kim JM (2019) "Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach" in Energies 2019, 12(17), 3310; https://doi.org/10.3390/en12173310 Retraction published: 09 November 2021

scholarly journals Real time control and monitoring of grid power systems using cloud computing

2019 ◽  
Vol 9 (2) ◽  
pp. 941 ◽  
Author(s):  
Nachiket Kulkarni ◽  
S. V. N. L. Lalitha ◽  
Sanjay A. Deokar
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Power System ◽  
Real Time ◽  
Monitoring And Control ◽  
Real Time Control ◽  
Grid Systems ◽  
The Real ◽  
Time Control ◽  
And Control

The use of grid power systems based on the combinations of various electrical networks, information technology, and communication layers called as Smart Grid systems. The technique of smart grid suppressed the problems faced by conventional grid systems such as inefficient energy management, improper control actions, grid faults, human errors, etc. The recent research on smart grid provides the approach for the real-time control and monitoring of grid power systems based on bidirectional communications. However, the smart grid is yet to improve regarding efficiency, energy management, reliability, and cost-effectiveness by considering its real-time implementation. In this paper, we present the real-time design of efficient monitoring and control of grid power system using the remote cloud server. We utilized the remote cloud server to fetch, monitor and control the real-time power system data to improve the universal control and response time. The proper hardware panel designed and fabricated to establish the connection with the grid as well as remote cloud users. The authenticated cloud users are provisioned to access and control the grid power system from anywhere securely. For the user authentication, we proposed the novel approach to secure the complete smart grid system. Finally, we demonstrated the effectiveness of real-time monitoring and control of the grid power method with the use of structure of practical framework.

scholarly journals Artificial Intelligence Techniques in Smart Grid: A Survey

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 548-568
Author(s):  
Olufemi A. Omitaomu ◽  
Haoran Niu
Keyword(s):  
Artificial Intelligence ◽  
Smart Grid ◽  
Power Systems ◽  
Power Grid ◽  
Grid Systems ◽  
Electric Power Grid ◽  
Type Data ◽  
Control Technologies ◽  
Advanced Metering ◽  
And Control

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

Smart Devices with Plug and Play Technique for Smart Grid Dispatch and Control System

2014 ◽  
Vol 521 ◽  
pp. 457-463 ◽  
Author(s):  
Rong Chang Yuan ◽  
Zhao Yun Deng ◽  
Li Xin Li ◽  
Yang Chun Hao ◽  
Fang Chun Di ◽  
...  
Keyword(s):  
Control System ◽  
Smart Grid ◽  
Smart Devices ◽  
Distribution Automation ◽  
Automation System ◽  
Plug And Play ◽  
Grid Systems ◽  
Smart Grid System ◽  
And Control ◽  
Automatic Systems

Smart Grid Systems mainly relies on many secondary automatic systems and information systems, such as Smart Grid Dispatch and Control System, Distribution Automation System, Automatic Safety Devices, Marketing System and etc. These systems are frequently incompatible with many devices and therefore waste much manpower for the compatibility. These systems cannot fulfill automatic configuration, auto-discovery, rapid reconstruction and etc. Plug and Play (PnP) stems from computer and Internet concept. This article bases on "Universal Plug and Play (UPnP)" concept, to build automatic identifying, automatic accessing mechanisms or system architecture in Smart Grid field, in order to realize automatic structuring for the secondary control system and information system, thus realize PnP and rapid restructure for the Smart Grid System, which bases on Smart Grid Dispatch and Control System.

scholarly journals Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

2021 ◽  
Author(s):  
Chethan Parthasarathy ◽  
Hossein Hafezi ◽  
Hannu Laaksonen
Keyword(s):  
Smart Grid ◽  
Network Management ◽  
Smart Grids ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Lithium Ion ◽  
Active Network ◽  
Li Ion ◽  
Grid Side ◽  
And Control

AbstractLithium-ion battery energy storage systems (Li-ion BESS), due to their capability in providing both active and reactive power services, act as a bridging technology for efficient implementation of active network management (ANM) schemes for land-based grid applications. Due to higher integration of intermittent renewable energy sources in the distribution system, transient instability may induce power quality issues, mainly in terms of voltage fluctuations. In such situations, ANM schemes in the power network are a possible solution to maintain operation limits defined by grid codes. However, to implement ANM schemes effectively, integration and control of highly flexible Li-ion BESS play an important role, considering their performance characteristics and economics. Hence, in this paper, an energy management system (EMS) has been developed for implementing the ANM scheme, particularly focusing on the integration design of Li-ion BESS and the controllers managing them. Developed ANM scheme has been utilized to mitigate MV network issues (i.e. voltage stability and adherence to reactive power window). The efficiency of Li-ion BESS integration methodology, performance of the EMS controllers to implement ANM scheme and the effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers have been validated by means of simulation studies in the Sundom smart grid network, Vaasa, Finland.

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