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RaPId: A modular and extensible toolbox for parameter estimation of Modelica and FMI compliant models
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTSLab)ORCID iD: 0000-0002-4125-1055
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTSLab)ORCID iD: 0000-0003-2353-1683
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTSLab)ORCID iD: 0000-0002-3312-9244
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTSLab)ORCID iD: 0000-0003-0988-7624
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2016 (English)In: SoftwareX, ISSN 2352-7110, Vol. 5, 144-149 p.Article in journal (Refereed) Published
Abstract [en]

This paper describes the Rapid Parameter Identification toolbox (RaPId), developed within the EU FP7 iTesla project. The toolbox was designed to carry out parameter identification on models developed using the Modelica language, focusing in particular on power system model identification needs. The toolbox has been developed with modularity and extensibility in mind, using Matlab/Simulink as a plug-in environment, where different tasks of the identification process are carried out. The identification process uses different optimization algorithms to improve the fitting of the model’s response to selected criteria. The modular architecture of RaPId gives users complete freedom to extend and adapt the software to their needs, e.g. to implement or link external solvers for simulation or optimization. The compatibility with Modelica models is brought by the use of technologies compliant with the Functional Mock-up Interface (FMI) standard.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 5, 144-149 p.
Keyword [en]
FMI; Modelica; Model validation; System identification
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-204927DOI: 10.1016/j.softx.2016.07.004OAI: oai:DiVA.org:kth-204927DiVA: diva2:1086914
Projects
iTESLA
Note

QC 20170519

Available from: 2017-04-04 Created: 2017-04-04 Last updated: 2017-05-19Bibliographically approved

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Vanfretti, LuigiBaudette, MaximeBogodorova, TetianaLavenius, JanGómez, Francisco José
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