Development of power system test bed for data mining of synchrophasors data, cyber-attack and relay testing in RTDS

Adhikari, Uttam; Morris, Thomas H.; Dahal, Nischal; Pan, Shengyi; King, Roger L.; Younan, Nicolas H.; Madani, Vahid

doi:10.1109/pesgm.2012.6345109

Cited by 17 publications

(17 citation statements)

References 15 publications

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“…The concept of the model (integration with other disciplines) [16, 18, 39, 45, 50-57, 63, 67, 68] The completeness and regularization of data acquisition variables [40,42,45,47,73,87] The optimization of related algorithms [58][59][60][61][62][63][64][65][66][67] The information fusion analysis [40,42,53,[69][70][71][72][73][74] The automation of process tools [33-35, 73, 75, 84, 85, 87] The visualization of work at each stage [5,11,55,61,[76][77][78][79]86] Practice testing and efficiency gains in large-scale real-world networks [80][81][82] The software engineering implementation of sensing methods [42,[83][84][85]88] The practical application of analysis and prediction results in specific fields [42,47,…”

Section: Status Of Foreign Researchmentioning

confidence: 99%

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Analysis framework of network security situational awareness and comparison of implementation methods

Huang

Wang

et al. 2019

J Wireless Com Network

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Information technology has penetrated into all aspects of politics, economy, and culture of the whole society. The information revolution has changed the way of communication all over the world, promoted the giant development of human society, and also drawn unprecedented attention to network security issues. Studies, focusing on network security, have experienced four main stages: idealized design for ensuring security, auxiliary examination and passive defense, active analysis and strategy formulation, and overall perception and trend prediction. Under the background of the new strategic command for the digital control that all countries are scrambled for, the discussion of network security situational awareness presents new characteristics both in the academic study and industrialization. In this regard, a thorough investigation has been made in the present paper into the literature of network security situational awareness. Firstly, the research status both at home and abroad is introduced, and then, the logical analysis framework is put forward concerning the network security situational awareness from the perspective of the data value chain. The whole process is composed of five successive stages: factor acquisition, model representation, measurement establishment, solution analysis, and situation prediction. Subsequently, the role of each stage and the mainstream methods are elaborated, and the application results on the experimental objects and the horizontal comparison between the methods are explained. In an attempt to provide a panoramic recognition of network security situational awareness, and auxiliary ideas for the industrialization of network security, this paper aims to provide some references for the scientific research and engineering personnel in this field.

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Section: Status Of Foreign Researchmentioning

confidence: 99%

“…In literature [45], the categories of sensors are divided into three categories: activity, configuration, and topology. In addition, in the specific field, the scope or type of collected information may be different [42,47,73,87]. (3).…”

Section: Status Of Foreign Researchmentioning

confidence: 99%

Analysis framework of network security situational awareness and comparison of implementation methods

Huang

Wang

et al. 2019

J Wireless Com Network

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“…RTDS is a platform for electromagnetic transient power system simulation with a typical size of 50 µs. Close to real time operation and large number of input/output channels of RTDS has been exploited to/for many power system applications recently [17]. It is an ideal tool for designing, testing and verification of algorithms for power systems protection and controls.…”

Section: A Test Systemmentioning

confidence: 99%

Machine learning based diagnosis support for ShipBoard Power Systems controls

Amgai

Shi

Santos

et al. 2013

2013 IEEE Electric Ship Technologies Symposium (ESTS)

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In this paper, a machine learning based decision support system for a naval shipboard power management system is proposed considering contingencies and load priority. A probabilistic model based Bayes' classifier is implemented to classify the current operation state of the ShipBoard Power System (SPS), depending upon the power system readiness for critical contingencies. Real power, reactive power, and generator status are taken as input features for the algorithm. Loss of vital/non-vital load is calculated by solving optimal power flow (OPF) to help build the knowledge base. Training data are updated online to increase the accuracy of the proposed approach. The characterization of the operation states helps the shipboard power management system to take the appropriate control action. Initial results from tests are presented and the outcomes from the particular techniques are discussed. Moreover, we also present RTDS based experimental framework towards the ongoing research on overall management system including the diagnosis support. Naïve Bayes' approach has classified the system states with 97.67% accuracy to new instances. Preliminary results show the computation time of this approach is in the order of 25 ms.

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“…Several CPS test beds have been developed in [14][15][16][17][18]. In [14], a test bed was developed for SCADA cyber security.…”

Section: Introductionmentioning

confidence: 99%

“…However, these test beds cannot run in real time or perform hardware-in-the-loop (HIL) simulation. A real time test bed was developed in [17] with the real time digital simulator (RTDS) and network analyzer, which can simulate denial of service (DoS) attacks. Authors in [18] developed a cyber-physical security test bed using RTDS, DIgSILENT and the internet-scale event and attack generation environment (ISEAGE).…”

Section: Introductionmentioning

confidence: 99%

Implementing a real-time cyber-physical system test bed in RTDS and OPNET

Chen

Butler‐Purry

Goulart

et al. 2014

2014 North American Power Symposium (NAPS)

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Numerous innovative smart grid technologies are deployed in modern power systems, making a power system a typical cyber-physical system (CPS). The increasing coupling between a physical power system and its communication network requires a smart grid simulator to run in a cyberphysical environment for cyber security research. In addition, smart grid technologies introduce numerous access points to the communication network, making cyber security a big concern in smart grid planning and operation. In this paper, a simple real time CPS test bed, implemented in RTDS and OPNET, is discussed. The setup of the test bed is introduced. Results of a case study simulated in the test bed to study the impact of cyber attacks on system transient stability are presented. The simple test bed was capable of accurately modelling a smart grid while providing user-friendly modeling experience.

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Development of power system test bed for data mining of synchrophasors data, cyber-attack and relay testing in RTDS

Cited by 17 publications

References 15 publications

Analysis framework of network security situational awareness and comparison of implementation methods

Analysis framework of network security situational awareness and comparison of implementation methods

Machine learning based diagnosis support for ShipBoard Power Systems controls

Implementing a real-time cyber-physical system test bed in RTDS and OPNET

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