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.

A Low Standby Power Consumption Control Circuit for Switching Power Supply

2014 ◽  
Vol 571-572 ◽  
pp. 893-896
Author(s):  
Zhu Lei Shao
Keyword(s):  
Power Consumption ◽  
Power Supply ◽  
Control Circuit ◽  
Switching Power Supply ◽  
Load Detection ◽  
Switching Power ◽  
Detection Circuit ◽  
Power Switches ◽  
Standby Power ◽  
Consumption Control

Aiming at reducing standby power consumption of switching power supply, a low standby power consumption control circuit for switching power supply is designed. The control circuit is composed of power switches, the driving circuit, the load detection circuit and the low power supply circuit. The control circuit effectively closed the input of switching power supply when the switching power supply is without load. The control circuit ensures the normal work of switching power supply when the switching power supply is with load. From the experiment results, the control circuit can effectively reduce standby power consumption of switching power supply.

Real-Time Monitoring of Smart Meters Based on Blockchain Technology

2022 ◽  
pp. 208-218
Author(s):  
K. Ramesh ◽  
Satya Dinesh Madasu ◽  
Idamakanti Kasireddy
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Power Supply ◽  
End Users ◽  
Smart Metering ◽  
Real Time Monitoring ◽  
Smart Meters ◽  
Grid Network ◽  
Blockchain Technology ◽  
Novel Technology

In this chapter, the authors primarily discuss how blockchain is being utilized in smarter grids across the globe and how some use cases can be a good fit as a technology. They ensure the reliability and uninterrupted power supply to end users by using smart metering in micro and macro grids, which is possible with novel technology that is transparent and without any cyberattacks/hackers: blockchain technology (BCT). In this chapter, BCT is implemented significantly at micro/macro smart grid network. Such a network would give efficient improvement and be interesting.

Real-time day ahead energy management for smart home using machine learning algorithm

2021 ◽  
pp. 1-12
Author(s):  
Nisha Vasudevan ◽  
Vasudevan Venkatraman ◽  
A Ramkumar ◽  
A Sheela
Keyword(s):  
Time Series ◽  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Learning Algorithm ◽  
Mathematical Formulation ◽  
Housing Sector ◽  
Grid Security ◽  
Smart Meters ◽  
Comparison Results

Smart grid is a sophisticated and smart electrical power transmission and distribution network, and it uses advanced information, interaction and control technologies to build up the economy, effectiveness, efficiency and grid security. The accuracy of day-to-day power consumption forecasting models has an important impact on several decisions making, such as fuel purchase scheduling, system security assessment, economic capacity generation scheduling and energy transaction planning. The techniques used for improving the load forecasting accuracy differ in the mathematical formulation as well as the features used in each formulation. Power utilization of the housing sector is an essential component of the overall electricity demand. An accurate forecast of energy consumption in the housing sector is quite relevant in this context. The recent adoption of smart meters makes it easier to access electricity readings at very precise resolutions; this source of available data can, therefore, be used to build predictive models., In this study, the authors have proposed Prophet Forecasting Model (PFM) for the application of forecasting day-ahead power consumption in association with the real-time power consumption time series dataset of a single house connected with smart grid near Paris, France. PFM is a special type of Generalized Additive Model. In this method, the time series power consumption dataset has three components, such as Trend, Seasonal and Holidays. Trend component was modelled by a saturating growth model and a piecewise linear model. Multi seasonal periods and Holidays were modelled with Fourier series. The Power consumption forecasting was done with Autoregressive Integrated Moving Average (ARIMA), Long Short Term Neural Memory Network (LSTM) and PFM. As per the comparison, the improved RMSE, MSE, MAE and RMSLE values of PFM were 0.2395, 0.0574, 0.1848 and 0.2395 respectively. From the comparison results of this study, the proposed method claims that the PFM is better than the other two models in prediction, and the LSTM is in the next position with less error.

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.

Privacy-Preserving Mining of Association Rules for Smart Grid

2014 ◽  
Vol 971-973 ◽  
pp. 1692-1695
Author(s):  
Huan Ren ◽  
Lu Li ◽  
Liu Sheng Huang ◽  
Wei Yang
Keyword(s):  
Data Mining ◽  
Smart Grid ◽  
Association Rules ◽  
Distribution Network ◽  
Privacy Preserving ◽  
Electricity Distribution ◽  
Individual Data ◽  
Smart Meters ◽  
Privacy Concerns ◽  
The Individual

The widespread deployment of smart meters for the modernization of the electricity distribution network has been associated with privacy concerns due to the potentially large number of measurements that reflect the consumers’ behavior. At the same time, how to extract important knowledge from the potentially large of measurements — these measurements are spilt among various parties, has already became a hot topic in the field of data mining. In this paper, we present protocols that can be used to compute meter measurements over defined sets of meters without revealing any additional about the individual meter readings, and address secure mining of association rules. Thus, most of the benefits of the smart grid can be achieved without revealing individual data.

scholarly journals Bilateral power supply of the traction network as a first stage of Smart Grid technology implementation in electric traction

2018 ◽  
Vol 180 ◽  
pp. 02003
Author(s):  
Mikołaj Bartłomiejczyk
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Research And Development ◽  
Power Supply ◽  
Technology Implementation ◽  
Grid Technology ◽  
Supply Network ◽  
Traction Network ◽  
Electric Traction ◽  
Smart Grid Technology

Since 2001, trolleybus system in Gdynia has been involved in many activities related to the reduction of power consumption, both in terms of implementation and research and development. In PKT, in cooperation with SESTO company, started applications of Smart Grid technologies in supply network: the bilateral supply. The paper presents results of this this novel investment.

scholarly journals Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Condition Monitoring ◽  
Resource Constraints ◽  
Detection System ◽  
Stable Operation ◽  
Detection Accuracy ◽  
Monitoring Method ◽  
Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

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.

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