scholarly journals Design and Development of Secured Communication Between Smart Meter and Neighborhood Gateway

2019 ◽  
pp. 378-384
Author(s):  
Kodamala Venkatesulu ◽  
G. Mamatha
Keyword(s):  
Power Consumption ◽  
New Technology ◽  
Denial Of Service ◽  
Substantial Reduction ◽  
Smart Meter ◽  
Smart Meters ◽  
Replay Attack ◽  
Load Limit ◽  
Communication Scheme ◽  
Short Time

A smart meter is an advanced meter which measures power consumption in much more accurately than a conventional meter and communicates the collected information back to the usage for load limit and tariff purposes. The objectives are privacy that nobody can obtain power usage of other person’s information if the protocol is accurately executed. Real time authentication that transmitted message can be real timely authorized by the receiver which is essential to resist against the denial of service (DoS) attack, Replay attack resistance that receiver can validate whether the received messages are the replay of previously authorized persons. The main objective of this new technology is the bidirectional flow of information. The smart meters send the power consumption reports to the power operator and also control instructions are sent from electricity board in order to be executed by the smart meters. In between, there consists of some gateways which are responsible for data accumulation. The main objective of the system is the communication of smart meter and neighborhood gateway. The presented communication scheme must consider the necessity for consumption reports transmission in short time intervals, and also it must consists of both security and the limited resources of smart meters. This implemented system demonstrates substantial reduction in storage space and data modifications are avoided.

scholarly journals Evaluation Model of Operation State Based on Deep Learning for Smart Meter

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4674
Author(s):  
Qingsheng Zhao ◽  
Juwen Mu ◽  
Xiaoqing Han ◽  
Dingkang Liang ◽  
Xuping Wang
Keyword(s):  
Deep Learning ◽  
Power Consumption ◽  
Detection Efficiency ◽  
Evaluation Model ◽  
Smart Meter ◽  
Smart Meters ◽  
Abnormal Detection ◽  
Prediction Residual ◽  
Threshold Setting ◽  
Training Efficiency

The operation state detection of numerous smart meters is a significant problem caused by manual on-site testing. This paper addresses the problem of improving the malfunction detection efficiency of smart meters using deep learning and proposes a novel evaluation model of operation state for smart meter. This evaluation model adopts recurrent neural networks (RNN) to predict power consumption. According to the prediction residual between predicted power consumption and the observed power consumption, the malfunctioning smart meter is detected. The training efficiency for the prediction model is improved by using transfer learning (TL). This evaluation uses an accumulator algorithm and threshold setting with flexibility for abnormal detection. In the simulation experiment, the detection principle is demonstrated to improve efficient replacement and extend the average using time of smart meters. The effectiveness of the evaluation model was verified on the actual station dataset. It has accurately detected the operation state of smart meters.

scholarly journals Implementation of Automatic Power Consumption Control in Smart Grid

2021 ◽  
Vol 9 (VII) ◽  
pp. 2138-2143
Author(s):  
Anitha. A
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Power Supply ◽  
Smart Meters ◽  
Good Communication ◽  
Communications Network ◽  
Load Limit ◽  
Proper Design ◽  
The Individual ◽  
Consumption Control

Transformation to Smart Grid needs proper design of good communication and monitoring infrastructure for the Smart meters as well as understanding the power use pattern of the individual users for providing them uniform power supply as per the individual consumer’s requirement.In the proposed system, the meter monitors and calculates the power and if the consumer exceeds the prescribed load limit it alarms. In case the consumer does not reduce his load meter automatically it cuts off the particular loads in consumer connection. GSM communications network are used to transfer electricity consumed data to the consumer as per programmed in the Arduino kit.

Modeling and Simulation of Smart Meters Based on Matlab/Simulink Software

2013 ◽  
Vol 846-847 ◽  
pp. 760-763
Author(s):  
Peng He Zhang ◽  
Cheng Dong Xiao ◽  
Yang Xue ◽  
Xin Lei Zhang
Keyword(s):  
Power Consumption ◽  
Power Grid ◽  
Prediction Method ◽  
Stable Operation ◽  
Smart Meter ◽  
Huge Number ◽  
Smart Meters ◽  
Smart Power ◽  
Matlab Simulink ◽  
Working Principle

Nowadays, smart meters are widely used in power grid, which plays an important role in building the smart power grid and its stability is the key to stable operation of the grid. However, the reliability prediction of the smart meters is difficult to be performed due to its huge number and it cannot be tested one by one. In order to study the prediction method, according to the working principle of smart meters, this paper presents a simulation smart meter model based on Matlab/Simulink software. And related experiments are performed to measure the power consumption under different loads, through comparing the measured power consumption between the simulation model and power analyzer, the correctness of the presented model is verified.

scholarly journals Thwarting Nonintrusive Occupancy Detection Attacks from Smart Meters

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Dapeng Man ◽  
Wu Yang ◽  
Shichang Xuan ◽  
Xiaojiang Du
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Real World ◽  
Side Effect ◽  
Smart Meter ◽  
Smart Meters ◽  
Occupancy Detection ◽  
Load Monitoring ◽  
Privacy Issues ◽  
Statistical Metrics

Occupancy information is one of the most important privacy issues of a home. Unfortunately, an attacker is able to detect occupancy from smart meter data. The current battery-based load hiding (BLH) methods cannot solve this problem. To thwart occupancy detection attacks, we propose a framework of battery-based schemes to prevent occupancy detection (BPOD). BPOD monitors the power consumption of a home and detects the occupancy in real time. According to the detection result, BPOD modifies those statistical metrics of power consumption, which highly correlate with the occupancy by charging or discharging a battery, creating a delusion that the home is always occupied. We evaluate BPOD in a simulation using several real-world smart meter datasets. Our experiment results show that BPOD effectively prevents the threshold-based and classifier-based occupancy detection attacks. Furthermore, BPOD is also able to prevent nonintrusive appliance load monitoring attacks (NILM) as a side-effect of thwarting detection attacks.

scholarly journals Hardware and Software Integration of an Electrophoretic display on a smart meter

2019 ◽  
Vol 29 ◽  
pp. 03003
Author(s):  
Sebastian Avram ◽  
Cătălin Daniel Căleanu ◽  
Radu Vasiu ◽  
Andreea-Mirela Safta ◽  
Horatiu George Belei
Keyword(s):  
Liquid Crystal ◽  
User Interface ◽  
Power Consumption ◽  
Low Cost ◽  
Liquid Crystal Displays ◽  
Smart Meter ◽  
Software Integration ◽  
Smart Meters ◽  
Lower Power ◽  
Electrophoretic Display

Electronic and smart electricity meters traditionally use as user interface liquid crystal displays due to low cost and proven technology. This paper presents the integration of a flexible electrophoretic display on a smart meter and the possible use cases of such a display. The two main benefit of EPD displays are image retention which can be used as read without power feature and lower power consumption compared to LCD for smart meters. The smart meters available on the market use batteriesor super capacitors for the read without power feature and require each 20ms tenths of mA to displayinformation on the LCD.

scholarly journals A novel multi-stage distributed authentication scheme for smart meter communication

2021 ◽  
Vol 7 ◽  
pp. e643
Author(s):  
Manjunath Hegde ◽  
Adnan Anwar ◽  
Karunakar Kotegar ◽  
Zubair Baig ◽  
Robin Doss
Keyword(s):  
Building Blocks ◽  
Energy System ◽  
Critical Energy ◽  
Data Availability ◽  
Impersonation Attack ◽  
Smart Meter ◽  
Smart Meters ◽  
Replay Attack ◽  
Insider Attack ◽  
Multi Stage

Smart meters have ensured effective end-user energy consumption data management and helping the power companies towards network operation efficiency. However, recent studies highlighted that cyber adversaries may launch attacks on smart meters that can cause data availability, integrity, and confidentiality issues both at the consumer side or at a network operator’s end. Therefore, research on smart meter data security has been attributed as one of the top priorities to ensure the safety and reliability of the critical energy system infrastructure. Authentication is one of the basic building blocks of any secure system. Numerous authentication schemes have been proposed for the smart grid, but most of these methods are applicable for two party communication. In this article, we propose a distributed, dynamic multistage authenticated key agreement scheme for smart meter communication. The proposed scheme provides secure authentication between smart meter, NAN gateway, and SCADA energy center in a distributed manner. Through rigorous cryptanalysis we have proved that the proposed scheme resist replay attack, insider attack, impersonation attack and man-in-the-middle attack. Also, it provides perfect forward secrecy, device anonymity and data confidentiality. The proposed scheme security is formally proved in the CK—model and, using BAN logic, it is proved that the scheme creates a secure session between the communication participants. The proposed scheme is simulated using the AVISPA tool and verified the safety against all active attacks. Further, efficiency analysis of the scheme has been made by considering its computation, communication, and functional costs. The computed results are compared with other related schemes. From these analysis results, it is proved that the proposed scheme is robust and secure when compared to other schemes.

Characteristics and Potential Application of Thermally Sprayed Thin Film Coatings

2000 ◽  
Author(s):  
M. Loch ◽  
G. Barbezat
Keyword(s):  
Thin Film ◽  
New Technology ◽  
Functional Coatings ◽  
Oxide Coatings ◽  
Film Coatings ◽  
Thin Film Coatings ◽  
Thermally Sprayed Coatings ◽  
Short Time ◽  
Thermally Sprayed ◽  
Sprayed Coatings

Abstract LPPS Thin Film is a new technology for the production of thin functional coatings. The coatings produced can fill the well known gap of coating thickness between conventional thin films (PVD, CVD and others) and conventional thermally sprayed coatings (Plasma, HVOF and others). The application is successful, if the advantages of the new technology (large areas can be dense coated within a very short time) are combined with the specific properties of thermally sprayed coatings to the benefit of the intended application. Beside the technology of LPPS Thin Film and it's characteristics the paper will summarise important properties of Alumina described in the literature and present some corresponding properties of Aluminium oxide coatings produced by LPPS Thin Film.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

scholarly journals Electric Consumption Assessment using Smart Meter Data and KPI Methodology

2020 ◽  
Vol 57 (3) ◽  
pp. 3-19
Author(s):  
A. Mutule ◽  
I. Zikmanis ◽  
A.-M. Dumitrescu
Keyword(s):  
State Of The Art ◽  
Residential Area ◽  
Electric Power System ◽  
Modern World ◽  
Specific Situation ◽  
Smart Meter ◽  
Smart Meters ◽  
The World ◽  
Study Case ◽  
Grid Operators

AbstractIn the modern world, many cities make use of state-of-the-art technologies for a diversity of applications. A field with very specific needs is the electric power system that deals with both large entities that govern themselves (grid operators) and the citizens. For both and all actors in between, there is an increased need for information. Steps to provide these data are always taken and several initiatives are ongoing across the world to equip residential users with last generation smart meters. However, a full deployment is still not possible. Considering this aspect, the authors propose KPIs for the specific situation when some information is available from the meters and other sources, but some is not. The study case is based on a residential area occupied mainly by university students and after an extensive measurement campaign the results have been studied and analysis methods proposed.

scholarly journals Mobile Application for Electric Power Monitoring on Energy Consumptions at a Campus University

2018 ◽  
Vol 11 (2) ◽  
pp. 637
Author(s):  
Murizah Kassim ◽  
Maisarah Abdul Rahman ◽  
Cik Ku Haroswati Che Ku Yahya ◽  
Azlina Idris
Keyword(s):  
Energy Consumption ◽  
Electric Power ◽  
Mobile Applications ◽  
Working Hours ◽  
Mobile App ◽  
Smart Meter ◽  
University Campus ◽  
Smart Meters ◽  
Power Monitoring ◽  
Energy Consumptions

This paper presents a research on electric power monitoring prototype mobile applications development on energy consumptions in a university campus. Electric power energy consumptions always are the issue of monitoring usage especially in a broad environment. University campus faces high used of electric power, thus crucial analysis on cause of the usage is needed. This research aims to analyses electric power usage in a university campus where implemented of few smart meters is installed to monitor five main buildings in a campus university. A Monitoring system is established in collecting electric power usage from the smart meters. Data from the smart meter then is analyzed based on energy consume on 5 buildings. Results presents graph on the power energy consume and presented on mobile applications using Live Code coding. The methodology involved the setup of the smart meters, monitoring and data collected from main smart meters, analyzed electrical consumptions for 5 buildings and mobile system development to monitor. A Live Code mobile app is designed then data collected from smart meter using ION software is published in graphs. Results presents the energy consumed for 5 building during day and night. Details on maximum and minimum energy consumption presented that show load of energy used in the campus. Result present Tower 1 saved most eenergy at night which is 65% compared to block 3 which is 8% saved energy although block 3 presents the lowest energy consumption in the working hours and non-working hours. This project is significant that can help campus facility to monitor electric power used thus able to control possible results in future implementations.

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