A multi-channel distributed routing scheme for smart grid real-time critical event monitoring applications in the perspective of Industry 4.0

2019 ◽  
Vol 32 (4) ◽  
pp. 236 ◽  
Author(s):  
Muhammad Faheem ◽  
Rizwan Aslam Butt ◽  
Basit Raza ◽  
Muhammad Waqar Ashraf ◽  
Md. A. Ngadi ◽  
...  
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Industry 4.0 ◽  
Critical Event ◽  
Event Monitoring ◽  
Distributed Routing ◽  
Routing Scheme ◽  
Monitoring Applications ◽  
Time Critical

scholarly journals A Survey on Vulnerabilities and Countermeasures in the Communications of the Smart Grid

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1881
Author(s):  
Jesús Lázaro ◽  
Armando Astarloa ◽  
Mikel Rodríguez ◽  
Unai Bidarte ◽  
Jaime Jiménez
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
International Electrotechnical Commission ◽  
Communication Infrastructure ◽  
Iec 61850 ◽  
Best Effort ◽  
Electrical Grid ◽  
Informational Technology ◽  
Iec 62351 ◽  
Time Critical

Since the 1990s, the digitalization process has transformed the communication infrastructure within the electrical grid: proprietary infrastructures and protocols have been replaced by the IEC 61850 approach, which realizes interoperability among vendors. Furthermore, the latest networking solutions merge operational technologies (OTs) and informational technology (IT) traffics in the same media, such as time-sensitive networking (TSN)—standard, interoperable, deterministic, and Ethernet-based. It merges OT and IT worlds by defining three basic traffic types: scheduled, best-effort, and reserved traffic. However, TSN demands security against potential new cyberattacks, primarily, to protect real-time critical messages. Consequently, security in the smart grid has turned into a hot topic under regulation, standardization, and business. This survey collects vulnerabilities of the communication in the smart grid and reveals security mechanisms introduced by international electrotechnical commission (IEC) 62351-6 and how to apply them to time-sensitive networking.

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

Real-time research lab in the Sundom smart grid pilot

2016 ◽  
Author(s):  
A. Monot ◽  
M. Wahler ◽  
J. Valtari ◽  
M. Rita-Kasari ◽  
J. Nikko
Keyword(s):  
Smart Grid ◽  
Real Time

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.

Real-Time Monitoring Applications for the Power Grid under Geomagnetic Disturbances

2020 ◽  
Author(s):  
Cecilia Klauber ◽  
Komal S. Shetye ◽  
Zeyu Mao ◽  
Thomas J. Overbye ◽  
Jennifer Gannon ◽  
...  
Keyword(s):  
Real Time ◽  
Power Grid ◽  
Real Time Monitoring ◽  
Geomagnetic Disturbances ◽  
Monitoring Applications

scholarly journals Evaluating Latency in Multiprocessing Embedded Systems for the Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3322
Author(s):  
Sara Alonso ◽  
Jesús Lázaro ◽  
Jaime Jiménez ◽  
Unai Bidarte ◽  
Leire Muguira
Keyword(s):  
Operating System ◽  
Smart Grid ◽  
Real Time ◽  
Processing System ◽  
The Other ◽  
Programmable Logic ◽  
Detailed Characterization ◽  
Timing Constraint ◽  
Time Part

Smart grid endpoints need to use two environments within a processing system (PS), one with a Linux-type operating system (OS) using the Arm Cortex-A53 cores for management tasks, and the other with a standalone execution or a real-time OS using the Arm Cortex-R5 cores. The Xen hypervisor and the OpenAMP framework allow this, but they may introduce a delay in the system, and some messages in the smart grid need a latency lower than 3 ms. In this paper, the Linux thread latencies are characterized by the Cyclictest tool. It is shown that when Xen hypervisor is used, this scenario is not suitable for the smart grid as it does not meet the 3 ms timing constraint. Then, standalone execution as the real-time part is evaluated, measuring the delay to handle an interrupt created in programmable logic (PL). The standalone application was run in A53 and R5 cores, with Xen hypervisor and OpenAMP framework. These scenarios all met the 3 ms constraint. The main contribution of the present work is the detailed characterization of each real-time execution, in order to facilitate selecting the most suitable one for each application.

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