Durchgängiges Anforderungsmanagement und Engineering für Smart Grid Lösungen

2020 ◽  
Vol 68 (9) ◽  
pp. 711-719
Author(s):  
Mathias Uslar
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Cyber Physical Systems ◽  
Industrie 4.0 ◽  
Internet Der Dinge ◽  
Physical Systems

ZusammenfassungIn diesem Beitrag wird die Notwendigkeit einer sinnvollen Definition und Klarstellung der Disziplin Energieinformatik aufgezeigt. Der Beitrag diskutiert verschiedene bestehende Definitionen und stellt sie in den Kontext des Anforderungsmanagements und der Lösungsfindung. Er motiviert die Notwendigkeit eines strukturierten disziplinären Ansatzes in der Energieinformatik auf der Grundlage bestehender Probleme und skizziert den aktuellen Stand des Stands der Wissenschaft und Technik, der hauptsächlich den systemtechnischen Anwendungsbereich für Smart Grids umfasst. Synergien mit anderen aktuellen Schwerpunktthemen wie Internet der Dinge (IoT), Industrie 4.0 (Digitalisierung der Produktion) und Cyber-Physical Systems (CPS) werden aus Anforderungssicht motiviert. Auf der Grundlage der aufgeworfenen Fragen und Herausforderungen werden neue sinnvolle Forschungsthemen für ein durchgängiges Anforderungsmanagement im Kontext Smart Grid diskutiert.

scholarly journals Classical Failure Modes and Effects Analysis in the Context of Smart Grid Cyber-Physical Systems

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1215
Author(s):  
Andrés A. Zúñiga ◽  
Alexandre Baleia ◽  
João Fernandes ◽  
Paulo Jose Da Costa Branco
Keyword(s):  
Smart Grid ◽  
Information And Communication Technologies ◽  
Asset Management ◽  
Smart Grids ◽  
Distribution Systems ◽  
Failure Modes ◽  
Cyber Physical Systems ◽  
Test System ◽  
Physical Systems ◽  
The Impact

Reliability assessment in traditional power distribution systems has played a key role in power system planning, design, and operation. Recently, new information and communication technologies have been introduced in power systems automation and asset management, making the distribution network even more complex. In order to achieve efficient energy management, the distribution grid has to adopt a new configuration and operational conditions that are changing the paradigm of the actual electrical system. Therefore, the emergence of the cyber-physical systems concept to face future energetic needs requires alternative approaches for evaluating the reliability of modern distribution systems, especially in the smart grids environment. In this paper, a reliability approach that makes use of failure modes of power and cyber network main components is proposed to evaluate risk analysis in smart electrical distribution systems. We introduce the application of Failure Modes and Effects Analysis (FMEA) method in future smart grid systems in order to establish the impact of different failure modes on their performance. A smart grid test system is defined and failure modes and their effects for both power and the cyber components are presented. Preventive maintenance tasks are proposed and systematized to minimize the impact of high-risk failures and increase reliability.

scholarly journals Classical Failure Modes and Effects Analysis in the Context of Smart Grid Cyber-Physical Systems

2020 ◽  
Author(s):  
Andrés A. Zúñiga ◽  
Alexandre Baleia ◽  
João Fernandes ◽  
Paulo Jose Da Costa Branco
Keyword(s):  
Smart Grid ◽  
Information And Communication Technologies ◽  
Asset Management ◽  
Smart Grids ◽  
Distribution Systems ◽  
Failure Modes ◽  
Cyber Physical Systems ◽  
Test System ◽  
Physical Systems ◽  
The Impact

Reliability assessment in traditional power distribution systems has played a key role in power system planning, design, and operation. Recently, new information and communication technologies have been introduced in power systems automation and asset management, making the distribution network even more complex. In order to achieve efficient energy management, the distribution grid has to adopt a new configuration and operational conditions that are changing the paradigm of the actual electrical system. Therefore, the emergence of the cyber-physical systems concept to face future energetic needs requires alternative approaches for evaluating the reliability of modern distribution systems, especially in the smart grids environment. In this paper, a reliability approach that makes use of failure modes of power and cyber network main components is proposed to evaluate risk analysis in smart electrical distribution systems. We introduce the application of Failure Modes and Effects Analysis (FMEA) method in future smart grid systems in order to establish the impact of different failure modes on their performance. A smart grid test system is defined and failure modes and their effects for both power and the cyber components are presented. Preventive maintenance tasks are proposed and systematized to minimize the impact of high-risk failures and increase reliability.

scholarly journals Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 487 ◽  
Author(s):  
Mahmoud Elsisi ◽  
Karar Mahmoud ◽  
Matti Lehtonen ◽  
Mohamed M. F. Darwish
Keyword(s):  
Machine Learning ◽  
Smart Grids ◽  
Industry 4.0 ◽  
Learning Algorithm ◽  
Cyber Physical Systems ◽  
The Internet ◽  
Smart Meters ◽  
Industrial Environment ◽  
Physical Systems ◽  
Smart Machines

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.

Smart grid cyber-physical systems: communication technologies, standards and challenges

2021 ◽  
Author(s):  
A. V. Jha ◽  
B. Appasani ◽  
A. N. Ghazali ◽  
P. Pattanayak ◽  
D. S. Gurjar ◽  
...  
Keyword(s):  
Smart Grid ◽  
Communication Technologies ◽  
Cyber Physical Systems ◽  
Physical Systems

Multicast Routing for Decentralized Control of Cyber Physical Systems with an Application in Smart Grid

2012 ◽  
Vol 30 (6) ◽  
pp. 1097-1107 ◽  
Author(s):  
Husheng Li ◽  
Lifeng Lai ◽  
H. Vincent Poor
Keyword(s):  
Smart Grid ◽  
Decentralized Control ◽  
Multicast Routing ◽  
Cyber Physical Systems ◽  
Physical Systems

scholarly journals A Dependable Time Series Analytic Framework for Cyber-Physical Systems of IoT-based Smart Grid

2019 ◽  
Vol 3 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Chang Wang ◽  
Yongxin Zhu ◽  
Weiwei Shi ◽  
Victor Chang ◽  
P. Vijayakumar ◽  
...  
Keyword(s):  
Time Series ◽  
Smart Grid ◽  
Cyber Physical Systems ◽  
Analytic Framework ◽  
Physical Systems

Adoption of Machine Learning With Adaptive Approach for Securing CPS

2020 ◽  
pp. 388-415
Author(s):  
Rama Mercy Sam Sigamani
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
Smart Grids ◽  
False Negative ◽  
False Negative Rate ◽  
Cyber Physical Systems ◽  
Detection Accuracy ◽  
Physical Systems ◽  
Positive Rate ◽  
Iot Devices

The cyber physical system safety and security is the major concern on the incorporated components with interface standards, communication protocols, physical operational characteristics, and real-time sensing. The seamless integration of computational and distributed physical components with intelligent mechanisms increases the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. In IoT-enabled cyber physical systems, cyber security is an essential challenge due to IoT devices in industrial control systems. Computational intelligence algorithms have been proposed to detect and mitigate the cyber-attacks in cyber physical systems, smart grids, power systems. The various machine learning approaches towards securing CPS is observed based on the performance metrics like detection accuracy, average classification rate, false negative rate, false positive rate, processing time per packet. A unique feature of CPS is considered through structural adaptation which facilitates a self-healing CPS.

Smart Grids: A Cyber–Physical Systems Perspective

2016 ◽  
Vol 104 (5) ◽  
pp. 1058-1070 ◽  
Author(s):  
Xinghuo Yu ◽  
Yusheng Xue
Keyword(s):  
Smart Grids ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Systems Perspective
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