In:
at - Automatisierungstechnik, Walter de Gruyter GmbH, Vol. 67, No. 12 ( 2019-11-18), p. 1035-1046
Abstract:
The energy transition entails a rapid uptake of renewable energy sources. Besides physical changes within the grid infrastructure, energy storage devices and their smart operation are key measures to master the resulting challenges like, e. g., a highly fluctuating power generation. For the latter, optimization based control has demonstrated its potential on a microgrid level. However, if a network of coupled microgrids is considered, iterative optimization schemes including several communication rounds are typically used. Here, we propose to replace the optimization on the microgrid level by using surrogate models either derived from radial basis functions or neural networks to avoid this iterative procedure. We prove well-posedness of our approach and demonstrate its efficiency by numerical simulations based on real data provided by an Australian grid operator.
Type of Medium:
Online Resource
ISSN:
2196-677X
,
0178-2312
DOI:
10.1515/auto-2019-0075
Language:
English
Publisher:
Walter de Gruyter GmbH
Publication Date:
2019
detail.hit.zdb_id:
629186-7
detail.hit.zdb_id:
2027287-X
SSG:
15,3
Permalink
