Details
| Translated title of the contribution | Integration of grid-serving modes of decentralized generation plants into computer-aided grid optimization to minimize the need for grid expansion measures |
|---|---|
| Original language | German |
| Pages (from-to) | 538-546 |
| Number of pages | 9 |
| Journal | Elektrotechnik und Informationstechnik |
| Volume | 138 |
| Issue number | 8 |
| Early online date | 1 Oct 2021 |
| Publication status | Published - Dec 2021 |
Abstract
The implementation of the Climate Action Programme of the German federal government will further increase the burden on the distribution grid level due to the further integration of decentralized generation plants. In this respect, rural medium-voltage grids are particularly burdened, since they have the highest proportion of directly connected decentralized generation plants with regard to the installed capacity. In addition to grid reinforcement and grid expansion measures, grid optimization measures are also implemented based on the NOVA principle (grid optimization before grid reinforcement before grid expansion) to prevent impermissible grid conditions. Consequently, grid optimization measures, which can also consist of grid-serving modes of decentralized generation plants, must be included to determine the optimal grid expansion measures. This paper describes an approach to use grid-serving modes of decentralized generation plants within a computer-aided grid optimization to minimize grid expansion measures in medium-voltage grids. The planning methodology, which consists of a matheuristic optimization approach coupling hybrid heuristics with an exact solution method, forms the basis of the grid optimization presented in this paper. The other focus is on the integration of grid-serving modes of decentralized generation plants into the exact solution method as well as on its mathematical description. The benefits of grid-serving modes to reduce the need for grid expansion are demonstrated by using sample calculations for a rural medium-voltage grid.
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
Sustainable Development Goals
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In: Elektrotechnik und Informationstechnik, Vol. 138, No. 8, 12.2021, p. 538-546.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Einbindung netzdienlicher Betriebsweisen dezentraler Erzeugungsanlagen in die rechnergestützte Netzoptimierung zur Minimierung des Netzausbaubedarfs
AU - Blaufuß, Christoph
AU - Hofmann, Lutz
PY - 2021/12
Y1 - 2021/12
N2 - The implementation of the Climate Action Programme of the German federal government will further increase the burden on the distribution grid level due to the further integration of decentralized generation plants. In this respect, rural medium-voltage grids are particularly burdened, since they have the highest proportion of directly connected decentralized generation plants with regard to the installed capacity. In addition to grid reinforcement and grid expansion measures, grid optimization measures are also implemented based on the NOVA principle (grid optimization before grid reinforcement before grid expansion) to prevent impermissible grid conditions. Consequently, grid optimization measures, which can also consist of grid-serving modes of decentralized generation plants, must be included to determine the optimal grid expansion measures. This paper describes an approach to use grid-serving modes of decentralized generation plants within a computer-aided grid optimization to minimize grid expansion measures in medium-voltage grids. The planning methodology, which consists of a matheuristic optimization approach coupling hybrid heuristics with an exact solution method, forms the basis of the grid optimization presented in this paper. The other focus is on the integration of grid-serving modes of decentralized generation plants into the exact solution method as well as on its mathematical description. The benefits of grid-serving modes to reduce the need for grid expansion are demonstrated by using sample calculations for a rural medium-voltage grid.
AB - The implementation of the Climate Action Programme of the German federal government will further increase the burden on the distribution grid level due to the further integration of decentralized generation plants. In this respect, rural medium-voltage grids are particularly burdened, since they have the highest proportion of directly connected decentralized generation plants with regard to the installed capacity. In addition to grid reinforcement and grid expansion measures, grid optimization measures are also implemented based on the NOVA principle (grid optimization before grid reinforcement before grid expansion) to prevent impermissible grid conditions. Consequently, grid optimization measures, which can also consist of grid-serving modes of decentralized generation plants, must be included to determine the optimal grid expansion measures. This paper describes an approach to use grid-serving modes of decentralized generation plants within a computer-aided grid optimization to minimize grid expansion measures in medium-voltage grids. The planning methodology, which consists of a matheuristic optimization approach coupling hybrid heuristics with an exact solution method, forms the basis of the grid optimization presented in this paper. The other focus is on the integration of grid-serving modes of decentralized generation plants into the exact solution method as well as on its mathematical description. The benefits of grid-serving modes to reduce the need for grid expansion are demonstrated by using sample calculations for a rural medium-voltage grid.
KW - grid extension optimization
KW - grid optimization
KW - grid planning
KW - grid planning methodology
KW - integration of renewable energies
KW - matheuristics
UR - http://www.scopus.com/inward/record.url?scp=85116241426&partnerID=8YFLogxK
U2 - 10.1007/s00502-021-00938-6
DO - 10.1007/s00502-021-00938-6
M3 - Artikel
AN - SCOPUS:85116241426
VL - 138
SP - 538
EP - 546
JO - Elektrotechnik und Informationstechnik
JF - Elektrotechnik und Informationstechnik
SN - 0932-383X
IS - 8
ER -