Enhancing Traditional Process SCADA and Historians for Industrial and Commercial Power Systems With Energy (Via IEC 61850)

Mazur, David C.; Entzminger, Rob A.; Kay, John

doi:10.1109/tia.2015.2463792

Cited by 13 publications

(11 citation statements)

References 12 publications

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“…In [27], the authors proposed an improved Historian structure that could handle large amounts of data. However, they used International Electrotechnical Commission 61850 protocol, which is an electricity domain-specific protocol, thus making the Historian not suitable for other industries.…”

Section: Interoperability and Historianmentioning

confidence: 99%

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Nicolae

Korodi

Silea

2019

Water

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Current efforts towards achieving better connectivity and increasing intelligence in functioning of industrial processes are guided by the Industrial Internet of Things paradigm and implicitly stimulate occurrence of data accumulation. In recent years, several researchers and industrial products have presented Historian application solutions for data accumulation. The large amounts of data that are gathered by these Historians remains mostly unused or used only for reporting purposes. So far, Historians have been focused on connectivity, data manipulation possibilities, and sometimes on low-cost solutions in order to gain higher applicability or to integrate multiple SCADA servers (e.g. Siemens–WinCC, Schneider Electric – Vijeo Citect, IGSS, Wonderware, InduSoft Web Studio, Inductive Automation – Ignition, etc.), etc. Both literature and industry are currently unable to identify a Historian solution that functions in fog and efficiently applies and is built upon Industry 4.0 ideas. The future is to conceive a proactive Historian that is able to, besides gathering data, identify dependencies and patterns for particular processes and elaborate strategies to increase performance in order to provide feedback through corrective action on the functional system. Using available solutions, determining patterns by the Historian operator in the context of big data is a tremendous effort. The motivation of this research is provided by the currently unoptimized and partly inefficient systems in the water industry that can benefit from cost reduction and quality indicator improvements through IIoT concepts related to data processing and process adjustments. As the first part of more complex research to obtain a proactive Historian, the current paper wishes to propose a reference architecture and to address the issue of data dependency analyses as part of pattern identification structures. The conceptual approach targets a highly customizable solution considering the variety of industrial processes, but it also underlines basic software modules as generally applicable for the same reason. To prove the efficiency of the obtained solution in the context of real industrial processes, and their corresponding monitoring and control solutions, the paper presents a test scenario in the water industry.

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Section: Interoperability and Historianmentioning

confidence: 99%

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Nicolae

Korodi

Silea

2019

Water

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“…Today's systems [1] and [4][5][6] demand a much higher level of communication to be available in smart-grid automation systems involving components like Intelligent Electronic Devices ( 1 IED's). IEDs [7,8] are designed to automate protection, control, monitoring and metering for the smart grid system in both peer-to-peer and client server implementation.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability Assessment and Experimentation of Smart Grid DNP3

Darwish

Igbe

Saadawi

2016

JCSM

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Smart-grids security is becoming a challenging research area that has emerged in recent years facing the energy sector. Threats are arising every day that could cause great scale of damages in critical infrastructure. Our paper will assess vulnerabilities pertaining to internal security threats associated with the smart grid. We will perform penetration testing using various attack scenarios in a simulated virtual environment involving DNP3 protocol. Vulnerability analysis and penetration testing involving Man-in-the-middle (MITM) attack will be addressed. Ultimately, by utilizing theoretical modeling of smart-grid attacks using game theory, we will be able to optimize our detection and mitigation strategies to reduce cyber threats in DNP3 environment. Intrusion detection system (IDS) will be necessary to identify attackers targeting the smart grid infrastructure. Mitigation techniques will ensure a healthy check of the network. Performing DNP3 vulnerabilities assessment, security attacks, detections, preventions and counter measures will be our goals to achieve in this research paper.

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“…The supervisory control and data acquisition (SCADA) system in addition to the technology of the wide area monitoring system (WAMS) can provide such massive voltage and power data in near real time [2]- [3]. Based on this vast amount of data, it is possible to define new appropriate analysis tools which can transfer the standard security and monitoring methods from static frameworks into dynamical frameworks [12].…”

Section: Introductionmentioning

confidence: 99%

Smart-Grid Topology Identification Using Sparse Recovery

Babakmehr

Simões

Wakin

et al. 2016

IEEE Trans. on Ind. Applicat.

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Smart grid (SG) technology reshapes the traditional power grid into a dynamical network with a layer of information that flows along the energy system. Recorded data from a variety of parameters in SGs can improve analysis of different supervisory problems, but an important issue is their cost and power efficiency in data analysis procedures. This paper develops an efficient solution for power network topology identification (PNTI) and monitoring activities in SG. The basic idea combines optimization-based sparse recovery techniques with a graph theory foundation. The power network (PN) is modeled as a large interconnected graph, which can be evaluated with the DC power-flow model. It has been shown that topology identification for such a system can mathematically be reformulated as a sparse recovery problem (SRP), and the corresponding SRP can efficiently be solved using SRP solvers. In this work we especially exploit the concentration of nonzero elements in the corresponding sparse vectors around the main diagonal in the nodal-admittance or structure matrix of the PN to improve the results. The network models have been generated with the MATPOWER toolbox, and Matlab-based simulation results have indicated the promising performance of the proposed method for real time TI in SGs.

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Enhancing Traditional Process SCADA and Historians for Industrial and Commercial Power Systems With Energy (Via IEC 61850)

Cited by 13 publications

References 12 publications

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Vulnerability Assessment and Experimentation of Smart Grid DNP3

Smart-Grid Topology Identification Using Sparse Recovery

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