Investigation of Fast, Secure and Reliable Network Restoration after Blackouts

Elmira Torabi Makhsos, Yi Guo, Wolfgang Gawlik, Benjamin Cox, Philipp Hinkel, Marian Zugck, Wolfram Wellßow, Robert Schmaranz, Ewald Traxler and Leopold Fiedler
Additional contact information
Elmira Torabi Makhsos: Institute of Energy Systems and Electrical Drives, Technische Universität Wien, 1040 Vienna, Austria
Yi Guo: Institute of Energy Systems and Electrical Drives, Technische Universität Wien, 1040 Vienna, Austria
Wolfgang Gawlik: Institute of Energy Systems and Electrical Drives, Technische Universität Wien, 1040 Vienna, Austria
Benjamin Cox: Institute of Energy Systems and Electrical Drives, Technische Universität Wien, 1040 Vienna, Austria
Philipp Hinkel: Division of Energy Systems and Energy Management, Technische Universität Kaiserslautern, 67663 Kaiserslautern, Germany
Marian Zugck: Division of Energy Systems and Energy Management, Technische Universität Kaiserslautern, 67663 Kaiserslautern, Germany
Wolfram Wellßow: Division of Energy Systems and Energy Management, Technische Universität Kaiserslautern, 67663 Kaiserslautern, Germany
Robert Schmaranz: KNG-Kärnten Netz GmbH, 9020 Klagenfurt am Wörthersee, Austria
Ewald Traxler: Netz Oberösterreich GmbH, 4030 Linz, Austria
Leopold Fiedler: Netz Oberösterreich GmbH, 4030 Linz, Austria

Energies, 2020, vol. 13, issue 11, 1-17

Abstract: Integrating distributed generation into power grids creates various technical challenges for network operation. Volatility of renewable energy resources may increase the probability of blackouts. In order to restore networks fast, securely and reliably after blackouts, within the research project RestoreGrid4RES’s network restoration strategies, the related issues caused by distributed generation are investigated and novel methods to face those challenges are developed. This paper focuses on (i) algorithms to identify possible restoration paths, (ii) key performance indicators for the assessment of grid restoration options and (iii) an evaluation of the results for network restoration strategies.

Keywords: power system restoration; distributed generation; optimization algorithm; key performance indicator (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/11/3019/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/11/3019/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:11:p:3019-:d:370355

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().