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 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 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.

scholarly journals A METHODOLOGY FOR CYBER HYGIENE IN SMART GRIDS

10.6036/10085 ◽  
2022 ◽  
Vol 97 (1) ◽  
pp. 92-97
Author(s):  
Juan Carlos Olivares Rojas ◽  
ENRIQUE REYES ARCHUNDIA ◽  
JOSE ANTONIO GUTIERREZ GNECCHI ◽  
ARTURO MENDEZ PATIÑO ◽  
JAIME CERDA JACOBO ◽  
...  
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Human Factor ◽  
Traditional Approach ◽  
Personal Hygiene ◽  
Grid Security ◽  
Smart Meters ◽  
Hygiene Practices ◽  
External Threats ◽  
Human Aspects

Although smart grids offer multiple advantages over traditional grids, there are still challenges to overcome to ensure the quality of service and grid security. In particular, cybersecurity plays an essential role in ensuring grid operation reliability and resilience to external threats. The traditional approach to address cybersecurity issues generally does not consider the human factor as the main component. Recently, the concept of cyber hygiene has emerged, where social and human aspects are fundamental to reduce vulnerabilities and the risk of attacks and breaches. In a similar manner to personal hygiene, which greatly influences people’s health, considering the human factor (i.e., human behaviour, awareness, and training) as a critical cybersecurity component, can significantly improve human operator cybersecurity practices that in turn can result in improved cybersecurity performance. In this paper, the authors propose and test a methodology for implementing cyber hygiene practices in the context of Smart Grid systems, focused on smart metering systems. The results suggest that implementing cyber hygiene practices can improve smart meter cybersecurity and be suitable for implementing other sensitive Smart Grid components. Key Words: Cybersecurity, Cyber Hygiene, Internet of Things, Smart Grid, Smart Meters.

scholarly journals Exploring the Privacy Issues of Smart-Grid Infrastructure – A Network Security Perspective

2019 ◽  
pp. 165-169
Keyword(s):  
Network Security ◽  
Smart Grid ◽  
Real Time ◽  
Smart Grids ◽  
Data Communication ◽  
Grid Infrastructure ◽  
Smart Meters ◽  
Holistic View ◽  
The Public ◽  
Public Networks

The proposed smart grid infrastructure aims to make use of the existing public networks such as internet for data communication between consumer premises to the public power utility network. The smart-grid adopts smart-meters which basically collect vast amount of data to provide a holistic view of the connected load behavior and preferences pattern related to power and water consumption. The smart-grids provide benefits to the utilities and consumers alike. For utilities the benefits are real time data collection, ease of power management, and reduced personnel requirement. The benefits for the users on the other hand include availability of real time usage data, providing information on ways to minimize power consumption, monetary savings and so on. Since, the smart-grid uses existing public networks the utilities do not have the burden of installing any new infrastructure (except for installing the smart-meters), thus an added advantage. But, the downside of using the public network is susceptibility to a variety of network attacks, if not guarded well against. This paper talks about the various network security vulnerabilities that exist and the measures to patch the same before employing in the smart grid networks.

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