Tool-assisted surrogate selection for simulation models in energy systems

• Autorzy: Balduin Stephan , Oest Frauke , Blank-Babazadeh Marita , Nieße Astrid , Lehnhoff Sebastian

Identyfikatory

DOI

10.15439/2019F242

• Konferencja: Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
• Języki publikacji: EN

Abstrakty

EN

Surrogate models have proved to be a suitable replacement for complex simulation models in various applications. Runtime considerations, complexity reduction and privacy concerns play a role in the decision to use a surrogate model. The choice of an appropriate surrogate model though is often tedious and largely dependent on the individual model properties. A tool can help to facilitate this process. To this end, we present a surrogate modeling process supporting tool that simplifies the process of generation and application of surrogate models in a co-simulation framework. We evaluate the tool in our application context, energy system co-simulation, and apply it to different simulation models from that domain with a focus on decentralized energy units.

Słowa kluczowe

EN

data privacy; optimisation; power engineering computing; power system security

PL

prywatność danych; optymalizacja; informatyka energetyczna; bezpieczeństwo systemu elektroenergetycznego

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2019
• Tom: Vol. 18
• Strony: 185--192
• Opis fizyczny: Bibliogr. 23 poz., tab., wz., wykr., rys.

Twórcy

autor

Balduin Stephan

• OFFIS – Institute for Information Technology, Oldenburg, Germany

autor

Oest Frauke

• OFFIS – Institute for Information Technology, Oldenburg, Germany

autor

Blank-Babazadeh Marita

• OFFIS – Institute for Information Technology, Oldenburg, Germany

autor

Nieße Astrid

• Leibniz University Hannover, Germany

autor

Lehnhoff Sebastian

• OFFIS – Institute for Information Technology, Oldenburg, Germany

Bibliografia

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Uwagi

1. This work is supported by the European Community’s Horizon 2020 Program (H2020/2014-2020) under project “ERIGrid” (Grant Agreement No. 654113).

2. Track 1: Artificial Intelligence and Applications

3. Technical Session: 7th International Workshop on Smart Energy Networks & Multi-Agent Systems

4. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).