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Multi-Domain Semantic Information and Physical Behavior Modeling of Power Systems and Gas Turbines Expanding the Common Information Model
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0001-8563-7112
Instituto Costaricense de Electricidad (ICE), San José, Costa Rica.
Statnett SF, Oslo, Norway.
2018 (English)In: IEEE Access, E-ISSN 2169-3536Article in journal (Refereed) Published
Abstract [en]

The rapid increase of Intermittent Energy Resources (IER) there is a need to have dispatchable production available to ensure secure operation and increase opportunity for energy system flexibility. Gas turbine-based power plants offer flexible operation that is being improved with new technology advancements. Those plants provide in general, quick start together with significant ramping capability, which can be exploited to balance IERs. Consequently, to understand this potential source of flexibility, better models for gas turbines are required for power systems studies and analysis. In this work both the required semantic information and physical behavior models of such multi-domain systems are considered. First, UML class diagrams and RDF schemas based on the Common Information Model (CIM) standards are used to describe the semantic information of the electrical power grid. An extension that exploits the ISO 15926 standard is herein proposed to derive the multi-domain semantics required by integrated electrical power grid with detailed gas turbine dynamic models. Second, the Modelica language is employed to create the equation-based models which represent the behavior of a multi-domain physical system. A comparative simulation analysis between the power system domain model and the multi-domain model has been performed. Some differences between the turbine dynamics representation of the commonly used GGOV1 standard model and a more detailed gas turbine model are shown.

Place, publisher, year, edition, pages
IEEE, 2018.
Keywords [en]
CIM, Cyber-Physical Systems, Dynamic Simulation, Equation-Based Modeling, IEC 61970, Information Modeling, ISO 15926, Modelica, Power Systems Simulation, Power Systems Modeling
National Category
Computer Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-239572DOI: 10.1109/ACCESS.2018.2882311ISI: 000454057400001Scopus ID: 2-s2.0-85057145801OAI: oai:DiVA.org:kth-239572DiVA, id: diva2:1265995
Note

QC 20181217

Available from: 2018-11-26 Created: 2018-11-26 Last updated: 2019-03-01Bibliographically approved

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Gómez, Francisco JoséVanfretti, Luigi

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