Figure 9 presents a block diagram of a power supply ‘rectifier type of converter’ (AC-DC) to power an electronic circuit in each smart electric meter of the proposed real-time power theft monitoring and detection system . The power supply consists of a step-down transformer (230 V AC to 18 V AC with 6 VA). With a full.
Figure 11presents a schematic diagram of the proposed real-time power theft monitoring and detection system with double connected data capture system that addresses both.
The proposed system utilizes the following methods to detect power theft attacks on the distribution feeders and consumer smart meters. The Arduino ATMega328P microcontroller on each smart meter is programmed to read the.
The proposed system features an internet of things (IoT) technology. This double metering system wirelessly auto-sends the captured electric data to.
Figure 12presents a scenario for consumer house F131: The circuit arrangement is that S1 (Switch-1) short-circuits the current sensor in the house so that the smart meter will.
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Beyond the specific context of electricity theft detection, the model can be utilized by power providers and stakeholders in the energy industry to reduce power losses. By accurately identifying instances of electricity theft, the suggested approach offers a valuable tool for combating fraudulent activities and minimizing financial losses in
Smart Power Theft Detection System Abstract: Power theft is normally done by two methods that is bypassing or hooking. So to detect it, a system (current measuring and comparing) is proposed in which the household distribution of current is done indirectly from the electric pole to an intermediate distributor box and then to the individual houses.
So, an Arduino Uno Based Automatic Power Theft Detection System is designed that aims to detect and measure power theft. In the designed system, whenever there will be a power theft the system
The main focus of this paper is to design a real-time power theft monitoring and detection system that is able to detect power theft in distribution systems. This proposed system utilizes smart
ElectricalEngineering Fig.4 Diagram of an IoT-based power theft analyser and detection Fig.5 Architecture of the smart metering system [34] not. The illegal connection is identified by comparing the
The game theory-based detection method establishes a game model based on the electricity theft user and the power company, and analyzes the behavior of the electricity theft user by simulating the evolution of the whole system. The core idea is a game equilibrium between the behavior of the electricity thief and the power system company.
In this paper, an electricity theft detection system is proposed based on a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) architecture. In this work, a robust CNN-LSTM model was investigated for electricity theft detection using historical power consumption data for 10,000 users. The dataset
Electricity theft may lead to energy spikes, large loads on electrical systems, significant revenue losses for the power provider, and hazards to public safety. The network-oriented methodology, the data-oriented technique, and a hybrid strategy that combines the two methods are the three distinct types of power theft detection strategies [3] .
The main focus of this paper is to design a real-time power theft monitoring and detection system that is able to detect power theft in distribution systems. This proposed system utilizes smart
Electricity theft comes with various disadvantages for power utilities, governments, businesses, and the general public. This continues despite the various solutions employed to detect and prevent it. Some of the
The proposed real-time power theft monitoring and detection system with a double metering system showed good simulation results to identify if there is meter tampering and illegal connections in the power system network [1]. At the same time, the hardware project showed how the smart electric meters of the proposed double metering system can be
The system described in this article provides a versatile solution for both postpaid and prepaid billing by utilising SEMs for power theft detection and automatic invoicing and substituting automated solutions for manual metres to improve energy management, provide ongoing oversight, and help to spot metre manipulation and electricity theft.
Power theft is one of the major problem in India. A large amount of energy is lost due to power theft and improper management. Therefore, it is required to design a system that would be able to detect the power theft as well as power theft location and take the necessary decision during normal and theft condition without any human interaction. This paper presents an efficient and
In addition, electricity theft behaviours can also affect the power system safety. For instance, the heavy load of electrical systems caused by electricity theft may lead to fires, which threaten the public safety. Therefore, accurate electricity theft detection is crucial for power grid safety and stableness.
Electricity theft is a global problem that negatively affects both utility companies and electricity users. It destabilizes the economic development of utility companies, causes electric hazards and impacts the high cost of energy for users. The development of smart grids plays an important role in electricity theft detection since they generate massive data that
Gupta and S. Sharma, "An IoT-based power theft detection and monitoring system for smart grids," in 2020 IEEE International Conference on Smart Grid and Clean Energy Technologies (ICSGCE), pp. 1-6, 2020. DOI: [10.1109/ICSGCE48840.2020.9240852]
Power theft is big issues in the field of electricity because it harms transmission lines and results in financial losses. So, it is important to detect electricity theft effectively. Kaur, R., Saini, G. (2023). Electricity Theft Detection System for Smart Metering Application Using Bi-LSTM. In: Rawat, S., Kumar, S., Kumar, P., Anguera, J
There are two drawbacks to using these systems based on this methodology: the accuracy and the infrastructure required to run them, such as smart energy meters, etc. Using the current analysis of the system, a new system can be proposed which aims to improve the accuracy of theft detection. Keywords: Include at least 4 keywords or phrases.
Power Theft Identification System Using Iot Abstract: Power theft is a blatant problem in electric powersystems, which causes great economic losses and leads to irregular supply of electicity.
Power theft, at low voltage distribution end is a concerning issue as the distribution companies lose billions of revenue annually. With the advent of smart grid technologies, smart meters with Information Communication Technology (ICT) can provide a solution for detecting and alerting the power theft. This paper presents the application of Internet of Things (IoT) in power theft
The future of IoT-based power theft detection system holds great promise. Here are some potential future scopes for such systems: Advanced Machine Learning Algorithms: Implementing more sophisticated machine learning algorithms for anomaly detection can enhance the accuracy of electricity theft identification, reducing false
To find the percentage of theft the difference between the power used and power stolen is calculated. The status of the power theft information is sent to electricity board and the consumer. In, Kumar Nalinaksh, et al., have proposed system for power theft detection system, based on a grid and power discoms. The proposed solution is used as an
Power theft is the most serious problem in recent years, causing huge losses to power companies. These situations are more common in countries like India; if we are prepared to prevent these thefts, we will save a lot of power. The electrical power theft detection system detects unauthorised distribution line tapping.
Non Technical Losses (NTL) is major problem in power system and cause big revenue losses to the electric utility. The Electricity Theft Detection (ETD) is important topic of research over the years and achieves great success in efficiently detecting the electricity thieves.
Keywords: electricity theft detection, anomaly detection, smart grid, machine learning, economic development. Citation: Iftikhar H, Khan N, Raza MA, Abbas G, Khan M, Aoudia M, Touti E and Emara A (2024) Electricity theft detection in smart grid using machine learning. Front. Energy Res. 12:1383090. doi: 10.3389/fenrg.2024.1383090
Power theft detection - Download as a PDF or view online for free. (AMR). If an AMR system via PLC is set in a power delivery system, a detection system for illegal electricity usage may be easily added in the
Electrical energy theft detection and prevention is one of the most appealing in the field of power distribution systems, and it remains a prime focus in the area of current research. Load profiles with the combination of support vector machine (SVM) demonstrate an automatic feature extraction technique, is explained in [ 2 ].
Meenal et al. [13] developed an IoT based system for power monitoring and theft detection. The system utilizes Raspberry pi board and a GSM module for sending the real time values of voltage and
Theft of electricity is a significant and growing global issue. India is one of many developing nations where electricity theft is a problem. The electrical power theft detection system is used to find unauthorized tapping on distribution lines. Meter tampering, unauthorized connections, and unpaid bills are all examples of electricity theft.
In this work, design and simulation of a system for power theft detection and alerting mechanism has been carried out. The theft is detected by using an observer meter and comparing the readings with that of the house hold meter. Consumer side energy is calculated and will be matched continuously in regular intervals with the units supplied by
Power theft is a blatant problem in electric powersystems, which causes great economic losses and leads to irregular supply of electicity. Power theft can be briefly defined as usage of power without the knowledge of the supplier. It has become the major problem in India and it is a crime. Overall India has highest losses about 16.2 billion dollar. Power theft can be happened in
Power Monitoring and Theft Detection System using IoT. R Meenal 1, Kevin M Kuruvilla 1, Adrin Denny 1, Rejin V Jose 1 and Renoy Roy 1. Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1362, International Conference on Physics and Photonics Processes in Nano Sciences 20–22 June 2019, Eluru, India Citation R
Power Theft Detection System (Review Paper) 1Papai Bhakta, 2Suman Debnath, 3Partha Debnath, 4Paramita Das,5Suparna Pal 1B. Tech Final year Students of JIS College Of Engineering 2Assistant Prof of JIS College Of 1,2,3.4.5 Department of Electrical Engineering,
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