Self-detection of New Photovoltaic Power Plants Using a Low Voltage Smart Grid System - Smart Energy Research: At the Crossroads of Engineering, Economics, and Computer Science Access content directly
Conference Papers Year : 2017

Self-detection of New Photovoltaic Power Plants Using a Low Voltage Smart Grid System

Philippe Steinbusch
  • Function : Author
  • PersonId : 1027010
Sebastian Fischer
  • Function : Author
  • PersonId : 1027011
Marcus Stötzel
  • Function : Author
  • PersonId : 1027012
Markus Zdrallek
  • Function : Author
  • PersonId : 1027013
Nils Neusel-Lange
  • Function : Author
  • PersonId : 1027014

Abstract

A rising amount of today’s distribution grids are equipped with smart grid systems to face the problems arising from the increasing use of decentralized and renewable energy sources. In comparison to conventional reinforced grids smart grid systems need to be maintained to stay up to date. Especially the installed photovoltaic (PV) power is a very important parameter for the system. Self-learning smart grid systems would reduce the maintenance efforts. A huge step towards this is a self-detection of new PV power plants in the grid. In this paper three methods to detect unknown PV plants in distribution grids are introduced. They are tested and validated in a use case. Additionally the influence of undetected PV power plants to the accuracy of the grid state identification is considered. Because of the huge impact of different factors only rudimentary results are presented and further investigations are focused.
Fichier principal
Vignette du fichier
450780_1_En_4_Chapter.pdf (195.65 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01691199 , version 1 (23-01-2018)

Licence

Attribution

Identifiers

Cite

Philippe Steinbusch, Sebastian Fischer, Marcus Stötzel, Markus Zdrallek, Nils Neusel-Lange. Self-detection of New Photovoltaic Power Plants Using a Low Voltage Smart Grid System. 3rd and 4th International Conference on Smart Energy Research (SmartER Europe 2016 and 2017), Feb 2016, Essen, Germany. pp.56-64, ⟨10.1007/978-3-319-66553-5_4⟩. ⟨hal-01691199⟩
96 View
83 Download

Altmetric

Share

Gmail Facebook X LinkedIn More