Co-Simulation Training Platform for Smart Grids

Strasser, Thomas; Stifter, Matthias; Andrén, Filip; Pálenský, Peter

doi:10.1109/tpwrs.2014.2305740

Cited by 61 publications

(32 citation statements)

References 32 publications

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“…Some universities have also created dedicated master courses with relevant topics. The instruction is performed with traditional methods, such as class lectures, but also with programming, advanced simulations [19] and laboratory exercises [2,6], where educational methods such as problem-based learning and experiential learning [8] are applied in some cases.…”

Section: Status Quo In Education and Trainingmentioning

confidence: 99%

“…Various software tools exist for simulationbased analysis of CPES. Review articles like [11,14,19] typically suggest that different tools are needed for different purposes. Also domains of expertise are wide spread, including electronics, ICT, automation, politics, economics, energy meteorology, sociology and much more.…”

Section: Laboratory Testsmentioning

confidence: 99%

“…Hands-on experience of using real equipment (renewalbes, controllable loads) can be obtained, whereby actual magnitudes are measured and real equipment is controlled. Morever, equipment that is not available in the laboratory environment can be simulated, which gives freedom to design experiments (see Figure 4) [8,16,19]. In addition, the performance of challenging tests in a safe and controllable environment is possible.…”

Section: Example: Hardware-in-the-loop Lab Coursementioning

confidence: 99%

See 2 more Smart Citations

Validating Intelligent Power and Energy Systems – A Discussion of Educational Needs

Kotsampopoulos

Hatziargyriou

Strasser

et al. 2017

Lecture Notes in Computer Science

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Abstract. Traditional power systems education and training is flanked by the demand for coping with the rising complexity of energy systems, like the integration of renewable and distributed generation, communication, control and information technology. A broad understanding of these topics by the current/future researchers and engineers is becoming more and more necessary. This paper identifies educational and training needs addressing the higher complexity of intelligent energy systems. Education needs and requirements are discussed, such as the development of systems-oriented skills and cross-disciplinary learning. Education and training possibilities and necessary tools are described focusing on classroom but also on laboratory-based learning methods. In this context, experiences of using notebooks, co-simulation approaches, hardware-inthe-loop methods and remote labs experiments are discussed.

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Section: Status Quo In Education and Trainingmentioning

confidence: 99%

Section: Laboratory Testsmentioning

confidence: 99%

Section: Example: Hardware-in-the-loop Lab Coursementioning

confidence: 99%

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Validating Intelligent Power and Energy Systems – A Discussion of Educational Needs

Kotsampopoulos

Hatziargyriou

Strasser

et al. 2017

Lecture Notes in Computer Science

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“…Such a testbed must involve realistic cyber (SDN) and physical (grid dynamics and operations) aspects for simulating the cyber-physical nature of the SDN-enabled smart grid. Although recent studies have developed various co-simulation testbeds based on power system simulators and network simulators (e.g., ns-2) [22,30], none of them have explored the implications and effects of a dynamically controllable communication network on a grid. Therefore, in the proposed testbed, we leverage Mininet, a popular OpenFlow-based SDN emulator, to emulate SDNbased smart grid communications; we leverage PowerWorld, a high-fidelity power generation and transmission system simulator, to simulate the physical aspects of power systems.…”

Section: An Sdn-enabled Smart Grid Testbedmentioning

confidence: 99%

Software-Defined Networking for Smart Grid Resilience

Dong

Lin

Tan

et al. 2015

Proceedings of the 1st ACM Workshop on Cyber-Physical System Security

135

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Software-defined networking (SDN) is an emerging networking paradigm that provides unprecedented flexibility in dynamically reconfiguring an IP network. It enables various applications such as network management, quality of service (QoS) optimization, and system resilience enhancement. Pilot studies have investigated the possibilities of applying SDN on smart grid communications, while the specific benefits and risks that SDN may bring to the resilience of smart grids against accidental failures and malicious attacks remain largely unexplored. Without a systematic understanding of these issues and convincing validations of proposed solutions, the power industry will be unlikely to embrace SDN, since resilience is always a key consideration for critical infrastructures like power grids. In this position paper, we aim to provide an initial understanding of these issues, by investigating (1) how SDN can enhance the resilience of typical smart grids to malicious attacks, (2) additional risks introduced by SDN and how to manage them, and (3) how to validate and evaluate SDN-based resilience solutions. Our goal is also to trigger more profound discussions on applying SDN to smart grids and inspire innovative SDN-based solutions for enhancing smart grid resilience.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org.

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“…Researchers at the Austrian Institute of Technology have developed a co-simulation training platform for education and training. In this platform, GribLAB-D is utilized to simulate the power system and NetSim has been used for communication network simulation [9]. In order to evaluate the real-time performance of Cyber-Physical system, a co-simulation platform called INSPIRE is presented in [10].…”

mentioning

confidence: 99%

Integrated simulation to analyze the impact of cyber-attacks on the power grid

Liu

Srivastava

2015

2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)

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With the development of the smart grid technology, Information and Communication Technology (ICT) plays a significant role in the smart grid. ICT enables to realize the smart grid, but also brings cyber vulnerabilities. It is important to analyze the impact of possible cyber-attacks on the power grid. In this paper, a real-time, cyber-physical co-simulation testbed with hardware-in-the-loop capability is discussed. Real-time Digital Simulator (RTDS), Synchrophasor devices, DeterLab, and a widearea monitoring application with closed-loop control are utilized in the developed testbed. Two different real life cyber-attacks, including TCP SYN flood attack, and man-in-the-middle attack, are simulated on an IEEE standard power system test case to analyze the the impact of these cyber-attacks on the power grid.

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Co-Simulation Training Platform for Smart Grids

Cited by 61 publications

References 32 publications

Validating Intelligent Power and Energy Systems – A Discussion of Educational Needs

Validating Intelligent Power and Energy Systems – A Discussion of Educational Needs

Software-Defined Networking for Smart Grid Resilience

Integrated simulation to analyze the impact of cyber-attacks on the power grid

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