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Energies 2017, 10(8), 1099; doi:10.3390/en10081099

A Large Scale Grid Data Analysis Platform for DSOs

1
Center for Energy - Electric Energy Systems, AIT Austrian Institute of Technology, Vienna 1210, Austria
2
Institute of Energy Systems and Electrical Drives, TU Wien, Vienna 1040, Austria
*
Author to whom correspondence should be addressed.
Received: 7 June 2017 / Revised: 14 July 2017 / Accepted: 14 July 2017 / Published: 27 July 2017

Abstract

The number of fluctuating distributed energy resources (DER) in electricity grids is continuously rising. Due to the lack of operational information on low-voltage (LV) networks, conservative assumptions are necessary to assess the connection of generators to the grid. This paper introduces the hosting capability (HC) as a measure to assess the amount of DER that can be integrated in LV-feeders. The HC of a feeder is the minimum amount of DER that can be hosted in a feeder without reinforcement needs for a given DER-scenario and for a given admissible voltage rise. The hosting capability assessment was performed on the entire LV-grid data of two Austrian Distribution System Operators (DSOs) with more than 36,000 LV-feeders. In total, 40 HC-scenarios were calculated with varying admissible voltage rise levels, DER-scenarios and reactive power control strategies. It turned out that only few feeder parameters such as the resistance at the end node and the lowest ampacity value of feeders show a high correlation with the calculated HC. Further, the impact of the DER-scenario on the share of voltage and loading constrained feeders is rather limited. The gathered results are suitable to validate equivalent LV-feeders models to perform integrated power flow studies on the transmission and distribution grids. Besides the results obtained for the network data of the two DSOs, a performant, modular and parallelizable tool has been developed to automatically analyze large LV network sets. View Full-Text
Keywords: low-voltage networks; hosting capacity; scalability; replicability analysis low-voltage networks; hosting capacity; scalability; replicability analysis
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Kadam, S.; Bletterie, B.; Gawlik, W. A Large Scale Grid Data Analysis Platform for DSOs. Energies 2017, 10, 1099.

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