A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

Davidson, E.M.; McArthur, S.D.J.; McDonald, James R.

doi:10.1109/tpwrs.2003.810981

Cited by 27 publications

(11 citation statements)

References 18 publications

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“…The use of SCL-based setting files can be extended to many other potential applications of automatic protection system analysis and design, including: protection testing [6], event and disturbance analysis [4], [5], protection coordination [35], and protection diagnostics and simulation [36]. Furthermore, adaptive protection schemes would also be significantly more practical to implement with standardized settings [8].…”

Section: B Enabling Protection Settings For Intelligent Applicationsmentioning

confidence: 99%

Enabling Efficient Engineering Processes and Automated Analysis for Power Protection Systems

Hong

Blair

Booth

et al. 2018

IEEE Systems Journal

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Abstract-The reliable operation of power networks depends on the correct configuration of protection systems. These systems involve the coordination of devices across a wide area, each with numerous setting parameters. Presently, protection settings data are typically stored in various vendor-specific proprietary formats, which are difficult to access, interchange, and manipulate automatically. Consequently, the engineering processes for implementing modern protection systems are extremely complex, involving multiple software tools from different vendors. This paper presents a novel solution to these challenges, through the use of the data model provided by the IEC 61850 standard, with the System Configuration description Language (SCL) format to represent protection settings data. The design of a Protection Setting data Conversion Tool (PSCT) that can automatically convert existing settings data between proprietary formats and the SCL-based format is presented. A case study of its implementation demonstrates the benefits of the common representation of protection settings for network operators and other stakeholders. The paper also addresses the challenges that network operators face in migrating to the new approach from existing legacy protection devices and data formats. Adoption of these recommendations and design approaches would shift protection systems from being largely single-vendor solutions to becoming efficient and truly open platforms, capable of supporting future intelligent applications and tools such as automated protection settings validation, diagnostics, and system simulation.

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Section: B Enabling Protection Settings For Intelligent Applicationsmentioning

confidence: 99%

Enabling Efficient Engineering Processes and Automated Analysis for Power Protection Systems

Hong

Blair

Booth

et al. 2018

IEEE Systems Journal

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“…Utilising knowledge elicited from protection experts, the TP interprets SCADA data in order to validate the correct operation of a protection scheme and distinguish the incorrect operations. Model based reasoning techniques were utilised in validating correct protection operations by the MBR toolkit [12]. DFR records were also analysed by an expert system in the Fault Record Identification software, developed in order to discover fault records which contain information relevant for further analysis.…”

Section: Monitoring At Sp Energy Networkmentioning

confidence: 99%

“…• A model-based reasoning engine for the validation of protection operation: The model-based reasoning (MBR) engine, which is part of an MBR toolset [12], implements a model-based approach to the analysis of DFR data [16]. The MBR engine propagates DFR data through a model of the protection scheme thus predicting the expected behaviour of the components of the scheme.…”

Section: A Legacy Intelligent Systemsmentioning

confidence: 99%

An automated fault analysis system for SP energy networks: Requirements, design and implementation

Napier

Davidson

McArthur

et al. 2009

2009 IEEE Power &Amp; Energy Society General Meeting

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The proliferation of monitoring equipment on modern electrical power transmission networks is causing an increasing amount of monitoring data to be captured by transmission network operators. Traditional manual data analysis techniques fail to meet the analysis and reporting requirements of the utilities which have chosen to invest in monitoring. The volume of monitoring data, the complexities in analysing multiple related data sources and the preparation of internal reports based on that analysis, render timely manual analysis impractical, if not intractable.In 2006, the authors reported on the first online trials of the protection engineering diagnostics agents (PEDA) system, an automated fault diagnosis system which integrated legacy intelligent systems for the analysis of SCADA and digital fault recorder (DFR) data in order to provide automatic post fault assessment of protection system performance.In this paper the authors revisit the requirements of the TNO where PEDA was trialled. Based on a new formal specification of requirements carried out in 2008, the authors discuss the requirements met by the current version of PEDA and how PEDA could be augmented to meet these new requirements highlighted in this latest analysis of the utilities' requirements.Index Terms-decision support systems, fault diagnosis, intelligent systems, knowledge-based systems, power transmission protection, multi-agent systems.

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“…A large body of work exists on diagnostics of electric power systems focusing on AC systems [5], as well as large vehicle systems. [12] examines the diagnostics for the international space station, [10] for an aircraft electric system, and [7] for a marine vehicle power system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic state estimation in distributed aircraft electric control systems via adaptive submodularity

Maillet

Özay

et al. 2013

52nd IEEE Conference on Decision and Control

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Abstract-We consider the problem of estimating the discrete state of an aircraft electric system under a distributed control architecture through active sensing. The main idea is to use a set of controllable switches to reconfigure the system in order to gather more information about the unknown state. By adaptively making a sequence of reconfiguration decisions with uncertain outcome, then correlating measurements and prior information to make the next decision, we aim to reduce the uncertainty. A greedy strategy is developed that maximizes the one-step expected uncertainty reduction. By exploiting recent results on adaptive submodularity, we give theoretical guarantees on the worst-case performance of the greedy strategy. We apply the proposed method in a fault detection scenario where the discrete state captures possible faults in various circuit components. In addition, simple abstraction rules are proposed to alleviate state space explosion and to scale up the strategy. Finally, the efficiency of the proposed method is demonstrated empirically on different circuits.

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A toolset for applying model-based reasoning techniques to diagnostics for power systems protection

Cited by 27 publications

References 18 publications

Enabling Efficient Engineering Processes and Automated Analysis for Power Protection Systems

Enabling Efficient Engineering Processes and Automated Analysis for Power Protection Systems

An automated fault analysis system for SP energy networks: Requirements, design and implementation

Dynamic state estimation in distributed aircraft electric control systems via adaptive submodularity

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