Change search
Refine search result
1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Baudette, Maxime
    et al.
    KTH.
    Castro, Marcelo
    Univ Fed Juiz de Fora, Juiz de Fora, Brazil..
    Rabuzin, Tin
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Lavenius, Jan
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Bogodorova, Tetiana
    Ukrainian Catholic Univ, Fac Appl Sci, Lvov, Ukraine..
    Vanfretti, Luigi
    Rensselaer Polytech Inst, Troy, NY 12180 USA..
    OpenIPSL: Open-Instance Power System Library - Update 1.5 to "iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations"2018In: Software Quality Professional, ISSN 1522-0540, Vol. 7, p. 34-36Article in journal (Refereed)
    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.

  • 2.
    Hohn, Fabian
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Rabuzin, Tin
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Wang, Jianping
    Nordström, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Distributed signal processing units for centralised substation protection and control2018In: The Journal of Engineering, ISSN 1872-3284, E-ISSN 2051-3305, Vol. 2018, no 15, p. 1223-1228Article in journal (Refereed)
    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.

  • 3.
    Rabuzin, Tin
    et al.
    KTH.
    Baudette, Maxime
    KTH.
    Vanfretti, Luigi
    Implementation of a Continuous Integration Workflow for a Power System Modelica Library2017In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE , 2017Conference 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.

  • 4.
    Rabuzin, Tin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Lavenius, Jan
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Taylor, Nathaniel
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Nordström, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Bayesian Detection of Islanding Events Using Voltage Angle Measurements2018In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018, IEEE, 2018, article id 8587561Conference 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.

  • 5.
    Vanfretti, Luigi
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Olsen, Svein
    Statnett SF, Oslo.
    Arava, Venkata Satya Narasinham
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Laera, Giuseppe
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Bidadfar, Ali
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Rabuzin, Tin
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Lavenius, Jan
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Baudette, Maxime
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Gómez, Francisco José
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Jakobsen, Sigurd H.
    Norwegian University of Science and Technology, Trondheim, Norway.
    An open data repository and a data processing software toolset of an equivalent Nordic grid model matched to historical electricity market data2017In: Data in Brief, E-ISSN 2352-3409, Vol. 11, p. 349-357Article in journal (Refereed)
    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.

  • 6.
    Vanfretti, Luigi
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Rabuzin, Tin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Baudette, Maxime
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Murad, M.
    iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations2016In: SoftwareX, ISSN 2352-7110Article in journal (Refereed)
    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.

  • 7.
    Zografos, Dimitrios
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Rabuzin, Tin
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Ghandhari, Mehrdad
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Eriksson, Robert
    Prediction of Frequency Nadir by Employing a Neural Network Approach2018In: 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Institute of Electrical and Electronics Engineers (IEEE), 2018Conference 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.

1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf