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Publications (7 of 7) Show all publications
Rabuzin, T., Lavenius, J., Taylor, N. & Nordström, L. (2018). Bayesian Detection of Islanding Events Using Voltage Angle Measurements. In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018: . Paper presented at 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018; Aalborg; Denmark; 29 October 2018 through 31 October 2018. IEEE, Article ID 8587561.
Open this publication in new window or tab >>Bayesian Detection of Islanding Events Using Voltage Angle Measurements
2018 (English)In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018, IEEE, 2018, article id 8587561Conference paper, Published paper (Refereed)
Abstract [en]

The growing presence of distributed generation in power systems increases the risk for the unintentional creation of electrical islands. It is important to apply reliable and quick is landing protection methods. At the same time, the deployment of phasor measurement units facilitates the usage of data-oriented techniques for the development of new wide-area protection applications, one of which is islanding protection. This paper presents a Bayesian approach to detecting an islanding event, which utilizes measurements of voltage angles at the system's buses. A model of mixtures of probabilistic principal component analysers has been fitted to the data using a variational inference algorithm and subsequently used for islanding detection. The proposed approach removes the need for setting parameters of the probabilistic model. The performance of the method is demonstrated on synthetic power system measurements.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-245971 (URN)10.1109/SmartGridComm.2018.8587561 (DOI)000458801500076 ()2-s2.0-85061060271 (Scopus ID)978-1-5386-7954-8 (ISBN)
Conference
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018; Aalborg; Denmark; 29 October 2018 through 31 October 2018
Note

QC 20190314

Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-05-10Bibliographically approved
Hohn, F., Rabuzin, T., Wang, J. & Nordström, L. (2018). Distributed signal processing units for centralised substation protection and control. The Journal of Engineering, 2018(15), 1223-1228
Open this publication in new window or tab >>Distributed signal processing units for centralised substation protection and control
2018 (English)In: The Journal of Engineering, ISSN 1872-3284, E-ISSN 2051-3305, Vol. 2018, no 15, p. 1223-1228Article in journal (Refereed) Published
Abstract [en]

Substation automation systems are characterised by a high degree of functional integration, which can lead to a centralised substation protection and control (CPC) architecture. Most CPC architectures utilise merging units to interface with current and voltage transformers, which causes a high-communication load on the process bus in case of large substations. This study proposes a CPC architecture based on distributed signal processing units (DSPUs) to overcome those drawbacks by publishing the results of the signal processing algorithms directly. The reduction of the communication load through the usage of DSPUs has been shown in a case study, which uses a 16-bay transmission substation topology as a reference.

Keywords
Data models, IEC standards, Signal processing, Substation protection, Substation automation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-241116 (URN)10.1049/joe.2018.0206 (DOI)
Note

QC 20190118

Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2019-05-10Bibliographically approved
Baudette, M., Castro, M., Rabuzin, T., Lavenius, J., Bogodorova, T. & Vanfretti, L. (2018). OpenIPSL: Open-Instance Power System Library - Update 1.5 to "iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations". Software Quality Professional, 7, 34-36
Open this publication in new window or tab >>OpenIPSL: Open-Instance Power System Library - Update 1.5 to "iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations"
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2018 (English)In: Software Quality Professional, ISSN 1522-0540, Vol. 7, p. 34-36Article in journal (Refereed) Published
Abstract [en]

This paper presents the latest improvements implemented in the Open-Instance Power System Library (OpenIPSL). The OpenIPSL is a fork from the original iTesla Power Systems Library (iPSL) by some of the original developers of the iPSL. This fork's motivation comes from the will of the authors to further develop the library with additional features tailored to research and teaching purposes. The enhancements include improvements to existing models, the addition of a new package of three phase models, and the implementation of automated tests through continuous integration.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV, 2018
Keywords
Modelica, Power systems, Simulation, Power system dynamics, Power system modeling
National Category
Environmental Engineering
Identifiers
urn:nbn:se:kth:diva-244166 (URN)10.1016/j.softx.2018.01.002 (DOI)000457139300007 ()
Note

QC 20190218

Available from: 2019-02-18 Created: 2019-02-18 Last updated: 2019-05-10Bibliographically approved
Zografos, D., Rabuzin, T., Ghandhari, M. & Eriksson, R. (2018). Prediction of Frequency Nadir by Employing a Neural Network Approach. In: 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe): . Paper presented at 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 21-25 Oct. 2018, Sarajevo, Bosnia-Herzegovina. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Prediction of Frequency Nadir by Employing a Neural Network Approach
2018 (English)In: 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper, Published paper (Refereed)
Abstract [en]

The increased integration rate of inverter-interfaced devices is affecting the frequency response of the modern power systems. This leads to an increase of the variability of the power generation and to a reduction of the total system's inertia. This evolution of the system necessitates the prediction of frequency metrics, so that the frequency stability of the system can be guaranteed and that necessary mitigation measures can be taken. This paper proposes a method to predict the frequency nadir by using a Neural Network (NN) approach. As the approach uses measurements during a first short time period after the event, it more accurately predicts the frequency nadir compared to using static values. Several inputs for the NN are examined and when the appropriate ones are selected, a highly accurate prediction is accomplished.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE PES Innovative Smart Grid Technologies Conference Europe, ISSN 2165-4816
Keywords
Frequency Response, Neural Network, Power System Dynamics, Power System Inertia, Renewable Energy Sources
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-241141 (URN)10.1109/ISGTEurope.2018.8571581 (DOI)000458690200066 ()2-s2.0-85060251220 (Scopus ID)978-1-5386-4505-5 (ISBN)
Conference
2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 21-25 Oct. 2018, Sarajevo, Bosnia-Herzegovina
Note

QC 20190117

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-05-10Bibliographically approved
Vanfretti, L., Olsen, S., Arava, V. S., Laera, G., Bidadfar, A., Rabuzin, T., . . . Jakobsen, S. H. (2017). An open data repository and a data processing software toolset of an equivalent Nordic grid model matched to historical electricity market data. Data in Brief, 11, 349-357
Open this publication in new window or tab >>An open data repository and a data processing software toolset of an equivalent Nordic grid model matched to historical electricity market data
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2017 (English)In: Data in Brief, E-ISSN 2352-3409, Vol. 11, p. 349-357Article in journal (Refereed) Published
Abstract [en]

This article presents an open data repository, the methodology to generate it and the associated data processing software developed to consolidate an hourly snapshot historical data set for the year 2015 to an equivalent Nordic power grid model (aka Nordic 44), the consolidation was achieved by matching the model׳s physical response w.r.t historical power flow records in the bidding regions of the Nordic grid that are available from the Nordic electricity market agent, Nord Pool.

The model is made available in the form of CIM v14, Modelica and PSS/E (Siemens PTI) files. The Nordic 44 model in Modelica and PSS/E were first presented in the paper titled “iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations” (Vanfretti et al., 2016) [1] for a single snapshot. In the digital repository being made available with the submission of this paper (SmarTSLab_Nordic44 Repository at Github, 2016) [2], a total of 8760 snapshots (for the year 2015) that can be used to initialize and execute dynamic simulations using tools compatible with CIM v14, the Modelica language and the proprietary PSS/E tool are provided. The Python scripts to generate the snapshots (processed data) are also available with all the data in the GitHub repository (SmarTSLab_Nordic44 Repository at Github, 2016) [2].

This Nordic 44 equivalent model was also used in iTesla project (iTesla) [3] to carry out simulations within a dynamic security assessment toolset (iTesla, 2016) [4], and has been further enhanced during the ITEA3 OpenCPS project (iTEA3) [5]. The raw, processed data and output models utilized within the iTesla platform (iTesla, 2016) [4] are also available in the repository. The CIM and Modelica snapshots of the “Nordic 44” model for the year 2015 are available in a Zenodo repository.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Electrical power systems; Electric power transmission; Smart grid; Power system modeling and simulation; Power system dynamics; Dynamic simulations; Power flow; Common Information Model (CIM); Modelica; Historical market data; Modeling; Simulation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-204928 (URN)10.1016/j.dib.2017.02.021 (DOI)2-s2.0-85013906901 (Scopus ID)
Projects
iTESLAOpenCPS
Note

QC 20170509

Available from: 2017-04-04 Created: 2017-04-04 Last updated: 2018-02-26Bibliographically approved
Rabuzin, T., Baudette, M. & Vanfretti, L. (2017). Implementation of a Continuous Integration Workflow for a Power System Modelica Library. In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING: . Paper presented at 2017 IEEE Power & Energy Society General Meeting, JUL 16-20, 2017, Chicago, IL. IEEE
Open this publication in new window or tab >>Implementation of a Continuous Integration Workflow for a Power System Modelica Library
2017 (English)In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

Traditional simulation tools for power system studies are, in general, shipped with built-in and closed model libraries. Typically, the models' implementation is not thoroughly documented, preventing the user to gain a full understanding of their implemented behavior. Previous efforts from the authors have focused on the development of an open source software library of power system components developed using Modelica: the Open-Instance Power System Library (OpenIPSL), which provides models that can easily be accessed and studied by the user. Recent developments have focused on the implementation of a software architecture facilitating collaborative developments on OpenIPSL. Employing the latest technologies available in the software development community, this paper details the implementation of a continuous integration workflow, providing automated testing and behavior verification of the library's models. This platform seeks to increase the library's stability and to provide more reliable models developed collaboratively by multiple individuals. Moreover, this software architecture only utilizes open source software, which can be hilly tailored to the specific needs of users and other library developers.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
Keywords
Modelica, continuous integration, testing, power system modeling, power system simulation, model validation
National Category
Software Engineering
Identifiers
urn:nbn:se:kth:diva-228183 (URN)000426921803073 ()2-s2.0-85046373974 (Scopus ID)978-1-5386-2212-4 (ISBN)
Conference
2017 IEEE Power & Energy Society General Meeting, JUL 16-20, 2017, Chicago, IL
Funder
VINNOVA
Note

QC 20180521

Available from: 2018-05-21 Created: 2018-05-21 Last updated: 2018-11-21Bibliographically approved
Vanfretti, L., Rabuzin, T., Baudette, M. & Murad, M. (2016). iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations. SoftwareX
Open this publication in new window or tab >>iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations
2016 (English)In: SoftwareX, ISSN 2352-7110Article in journal (Refereed) Published
Abstract [en]

The iTesla Power Systems Library (iPSL) is a Modelica package providing a set of power system components for phasor time-domain modeling and simulation. The Modelica language provides a systematic approach to develop models using a formal mathematical description, that uniquely specifies the physical behavior of a component or the entire system. Furthermore, the standardized specification of the Modelica language (Modelica Association [1]) enables unambiguous model exchange by allowing any Modelica-compliant tool to utilize the models for simulation and their analyses without the need of specific mediator. As the Modelica language is being developed with open specifications, any tool that implements these requirements can be utilized. This gives users the freedom of choosing an Integrated Development Environment (IDE) of their choice. Furthermore, any integration solver can be implemented to simulate Modelica models. Additionally, Modelica is an object-oriented language, enabling code factorization and model re-use to improve the readability of a library by structuring it with object-oriented hierarchy. The developed library is released under an open source license to enable a wider distribution and let the user customize it to their specific needs.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Modelica, Power system, Simulation
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-188211 (URN)10.1016/j.softx.2016.05.001 (DOI)2-s2.0-84971435087 (Scopus ID)
Note

QC 20160609

Available from: 2016-06-08 Created: 2016-06-08 Last updated: 2016-12-22Bibliographically approved
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4736-4760

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