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http://dx.doi.org/10.18419/opus-12503
Autor(en): | Eisenmann, Adrian Streubel, Tim Rudion, Krzysztof |
Titel: | Power quality mitigation via smart demand-side management based on a genetic algorithm |
Erscheinungsdatum: | 2022 |
Dokumentart: | Zeitschriftenartikel |
Seiten: | 24 |
Erschienen in: | Energies 15 (2022), No. 1492 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-125221 http://elib.uni-stuttgart.de/handle/11682/12522 http://dx.doi.org/10.18419/opus-12503 |
ISSN: | 1996-1073 |
Zusammenfassung: | In modern electrical grids, the number of nonlinear grid elements and actively controlled loads is rising. Maintaining the power quality will therefore become a challenging task. This paper presents a power quality mitigation method via smart demand-side management. The mitigation method is based on a genetic algorithm guided optimization for smart operational planning of the grid elements. The algorithm inherits the possibility to solve multiple, even competing, objectives. The objective function uses and translates the fitness functions of the genetic algorithm into a minimization or maximization problem, thus narrowing down the complexity of the addressed high cardinality optimization problem. The NSGA-II algorithm is used to obtain feasible solutions for the auto optimization of the demand-side management. A simplified industrial grid with five different machines is used as a case study to showcase the minimization of the harmonic distortion to normative limits for all time steps during a day at a specific grid node, while maintaining the productivity of the underlying industrial process. |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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energies-15-01492-v3.pdf | 6,66 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons