A Comprehensive Review of Practical Issues for Interoperability Using the Common Information Model in Smart Grids

Kim, Hyun Joong; Jeong, Chang Min; Sohn, Jin-Man; Joo, Jin Chul; Donde, Vaibhav; Ko, Youngmi; Yoon, Yong Tae

doi:10.3390/en13061435

Cited by 21 publications

(12 citation statements)

References 84 publications

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“…Researchers have worked towards developing models for novel devices such as energy routers [6], electric vehicles (EVs) [23], smart meters [24] or new smart grid applications such as virtual power plants [4], EV charging coordination schemes [3]. "The main reasons behind such a positive uptake are object-oriented modeling that allows for simple yet strong device modeling, interoperable communication systems that do not depend on certain company or a technology as well as robust message exchange services that are developed for power system applications [25]. As shown in Figure 1, there are three services utilized.…”

Section: Iec 61850 Goose Messages and Cybersecurity Vulnerabilitiesmentioning

confidence: 99%

Machine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messages

et al. 2021

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Increased connectivity is required to implement novel coordination and control schemes. IEC 61850-based communication solutions have become popular due to many reasons—object-oriented modeling capability, interoperable connectivity and strong communication protocols, to name a few. However, communication infrastructure is not well-equipped with cybersecurity mechanisms for secure operation. Unlike online banking systems that have been running such security systems for decades, smart grid cybersecurity is an emerging field. To achieve security at all levels, operational technology-based security is also needed. To address this need, this paper develops an intrusion detection system for smart grids utilizing IEC 61850’s Generic Object-Oriented Substation Event (GOOSE) messages. The system is developed with machine learning and is able to monitor the communication traffic of a given power system and distinguish normal events from abnormal ones, i.e., attacks. The designed system is implemented and tested with a realistic IEC 61850 GOOSE message dataset under symmetric and asymmetric fault conditions in the power system. The results show that the proposed system can successfully distinguish normal power system events from cyberattacks with high accuracy. This ensures that smart grids have intrusion detection in addition to cybersecurity features attached to exchanged messages.

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Section: Iec 61850 Goose Messages and Cybersecurity Vulnerabilitiesmentioning

confidence: 99%

Machine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messages

et al. 2021

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“…Researchers have worked towards developing models for novel devices such as electric vehicles (EVs) [27] and smart meters [28] or new smartgrid applications such as virtual power plants [4], EV charging coordination schemes [3]. The main reasons behind such a positive uptake are object-oriented modeling that allows for simple yet strong device modeling, interoperable communication systems that do not depend on certain company or a technology as well as robust message exchange services that are developed for power system applications [29]. As shown in Figure 1, there are three services utilized.…”

Section: Iec 61850 Sv Messages and Cybersecurity Vulnerabilitiesmentioning

confidence: 99%

Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values Under Symmetric and Asymmetric Faults

et al. 2021

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“…Additionally, CIM extensions have been proposed for distributed resources, [9], [10], distribution network management [11], [12], and for advanced distribution applications such as asset management, fault location, and power monitoring [13]. For interoperability and to be used by advanced portable applications, models and data should be validated and the process of validation should be efficient and timely [14]. However, distribution systems models are error prone and model accuracy is elusive due to:…”

Section: Introductionmentioning

confidence: 99%

Admittance Matrix Validation for Power Distribution System Models Using a Networked Equipment Model Framework

et al. 2022

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The evolving nature of electric power distribution systems is motivating the development of advanced applications for utility planning, operation, management, and control. These model-based applications interact with multiple subsystems within software platforms referred to as advanced distribution management systems. Recently, the Common Information Model has been used to enable data model standardization across several entities. Model fidelity is the key to the development of leading-edge, scalable model-based algorithms and assessment of emerging technologies such as distributed energy resources for grid planning and operation. However, distribution system models are error-prone and model validation is challenging due to: (1) the need for considerable time and effort to maintain the network models, (2) update delays due to the evolving nature of the real-world systems that models are derived from, and (3) inevitable human errors in the process which are difficult to detect. In this paper, we extend a model validation application from our prior work referred to as the Model Validator to derive and validate a system admittance matrix using the Common Information Model. First, we introduce different modules for computing device-level primitive admittance matrices from Common Information Model parameters. These individual primitive admittance matrices are then used to validate corresponding entries in a full system admittance matrix. In addition, we validate the overall system admittance matrix by checking for gaps in coverage or extra elements that are not expected. The proposed approach checks the validity of each piece of network model equipment separately and identifies inconsistencies between Common Information Model parameters and the system admittance matrix at the device level. Furthermore, where devices can be specified using different combinations of Common Information Model parameters, each parameter combination is validated separately. This breakdown can help distribution engineers more efficiently apply root cause analysis for inconsistencies. The Model Validator application is implemented on top of GridAPPS-D, an open-source standards-based platform for advanced distribution management system application development. The effectiveness of the proposed application is demonstrated on six different test cases: four IEEE feeders, the Electric Power Research Institute J1 circuit, and a taxonomy feeder.INDEX TERMS Common information model, model checking, network topology, power distribution, power system modeling, system validation. NOMENCLATUREA.

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A Comprehensive Review of Practical Issues for Interoperability Using the Common Information Model in Smart Grids

Cited by 21 publications

References 84 publications

Machine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messages

Machine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messages

Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values Under Symmetric and Asymmetric Faults

Admittance Matrix Validation for Power Distribution System Models Using a Networked Equipment Model Framework

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