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Innovative grid optimization approach based on artificial neural networks

  • We present an innovative decision support system (DSS) for distribution system operators (DSO) based on an artificial neural network (ANN). A trained ANN has the ability to recognize problem patterns and to propose solutions that can be implemented directly in real time grid management. The principle functionality of this ANN based optimizer has been demonstrated by means of a simple virtual electrical grid. For this grid, the trained ANN predicted the solution minimizing the total line power dissipation in 98 percent of the cases considered. In 99 percent of the cases, a valid solution in compliance with the specified operating conditions was found. First ANN tests on a more realistic grid, calibrated with household load measurements, revealed a prediction rate between 88 and 90 percent depending on the optimization criteria. This approach promises a faster, more cost-efficient and potentially secure method to support distribution system operators in grid management.

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Author:Adrian Wenzel, Manuela Linke, Tobias Messmer, Gabriel Micard, Gunnar Schubert, Adrian Minde, Matthias Kindl
Parent Title (English):IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 29 Sept.-2 Oct. 2019, Bucharest, Romania
Document Type:Conference Proceeding
Year of Publication:2019
Release Date:2020/01/28
Tag:Artificial Neural Network; Decision Support System; Distribution Grid Management; Smart Grid
Page Number:4
Volltextzugang für Angehörige der Hochschule Konstanz möglich.
Institutes:Fakultät Elektrotechnik und Informationstechnik
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (German):License LogoUrheberrechtlich geschützt