Series of articles on the characterisation of low-voltage grids and grid representatives: Identification of grid clusters in the low voltage level

Many research projects in the context of the electrification of mobility, heat and industry are investigating how new electrical consumers in combination with the ramp-up of renewable energies will affect electricity grids. A large share of the added electrical load is connected in low-voltage grids (LV grids). One approach for their integration is to make consumption behavior more flexible in order to avoid or eliminate congestions in the grid. To evaluate the concepts in terms of their impact on the grids, they are simulated with future load scenarios and grid operation strategies.

In total, there are over 500,000 LV grids in Germany, which are operated by around 800 distribution grid operators [1]. In total, these result in a line length of over 1,200,000 km [2]. It is hardly possible to simulate all grids individually. On the one hand, they are not available in a simulatable form, and on the other hand, this would require an enormous amount of computation capacity. In order to be able to make statements for different grid structures in Germany, reference grids are therefore used for simulations. These allow to draw conclusions about the grid infrastructure from geographical and structural parameters.

This series of articles shows which parameters and methods are used to create reference grids. Furthermore, data from literature is merged and a set of reference grids is created. Specifically, the following topics are addressed:

  1. Low-voltage grids in Germany
  2. Characterisation of low-voltage grids
  3. Identification of grid clusters in the low voltage level
  4. Identification of reference grids for the clusters
  5. Distribution grids in the Climate-Neutral Energy System – Scenarios for Consumption, Generation and Grid Operation

Description of low-voltage grids

As the second article in the series of contributions has made clear, there are various parameters that are suitable for the characterisation of low-voltage grids (LV grids). In the literature, clusters have already been identified or defined which allow a characteristic classification of grid areas based on structural parameters. These clusters were compared within the framework of the meta-analysis carried out and combined to form “meta-clusters”. The aim of this process was to link the clusters from the literature, considering the smallest possible number of key parameters, in order to ensure the simplest possible transferability from this. The clusters and network types described in the following sources were used:

  • the studies [3], [4], [5], [6] and [7] examine grids and divide them into clusters,
  • Studies [8] and [9] examine area structures and create typical grids for them.

Furthermore, 1,200 real LV grids were analysed in the context of the clusters in order to verify the meta-clusters formed from the literature, resulting in a total of 18 meta-clusters (cf. Figure 1).


Figure 1 Meta-cluster for low-voltage grids and values of descriptive parameters

As the table illustrates, the identified meta-clusters are identified using three parameters normalised to the grid connection points (GCP), resulting in bandwidths in each case, which in combination form a “primary key”:

  • Transformer rating per GCP
  • Distance to the nearest neighbour/line length per GCP
  • Number of apartments/commercial units per GCP

The calculated bandwidths or primary keys thus span a cuboid in the three-dimensional space of the parameters for each cluster. Figure 2 illustrates the location of the clusters in this definition space and shows how they are delineated from each other. It becomes clear that the identified clusters show clear differences in their dimensions and that they do not completely fill the definition space shown (free spaces between the cluster cuboids). There are also local clusters in the definition space shown. These characteristics are due to several factors. For example, the grid areas studied in the literature and the clusters identified from them often focus on a specific type of area or region, which is ultimately reflected in local clusters. The definition of the size of the clusters is subject to the methodological approach selected in each case. LV distribution networks are also very diverse in their structure, whereby supra-regional tendencies can be identified from the clusters and the settlement structure encompassing the grids, such as terraced house settlements (low building/line distances with a simultaneously low number of apartments per GCP).

Figure 2 Meta-Clusters for low-voltage grids in three dimensional space

The meta-clusters identified in the literature and verified by network data of real distribution grids were characterised and delimited from each other in characteristics. In the following, two meta-clusters are described based on the characteristics drawn up. The meta cluster “Low-density residential Area B” describes a residential settlement consisting of single-family houses and duplexes. Therefore, the number of apartments is low with an average of 1 – 2.5 apartments per GCP. The area structure of the meta-cluster is diverse: the grids serve residential areas of small municipalities, towns or even outlying districts of large German cities. The distance between the GCP in the grids of this cluster is between 30 ‑ 50 m. Thus, it can be assumed that the buildings are not directly adjacent to each other, but that corresponding areas on the properties between the buildings are free (e.g. gardens) or are built up with buildings irrelevant for distribution grids (e.g. garages). The transformer rating per GCP is 4 – 10 kVA, which is in the middle range of the identified definition space. This is because in distribution grids in this cluster, the commercial share is low and larger commercial consumers tend to be atypical in these grids. In addition, the transformer size is influenced by other factors such as the year of construction of the residential area. Compared to all other clusters, the installed PV capacity in grids in this cluster is at an average level. Compared to clusters and grids that primarily supply housing estates, the installed PV capacity is at a comparatively high level. Figure 3 summarises the characteristics of the cluster “Low‑density residential Area B” on the left.

Figure 3 Profiles of the two clusters "Low-density residential area B" and "Commercial area A”

The meta cluster “commercial area A” represents an area whose primary supply task is focused on commercial businesses and smaller industrial companies. This means that the share of residential buildings in the grid is very low. The number of residential units or businesses per GCP is low and the distance between buildings is relatively large (settlement structure with low density). A specific feature of the “commercial area A” is the particularly large rated power of the transformer, which distinguishes this commercial cluster from the other two commercial clusters. Furthermore, grids in this cluster have high installed PV capacity per GCP. Typical grids in this cluster are small commercial grids with few electricity-intensive buildings, e.g. farms with a central grid connection point and PV-built warehouses/stables.

The profiles of the 18 meta-clusters can be found in the download area below. The following article in this series focuses on the methodological procedure for modelling characteristic distribution grids (“benchmark grids”) for each of the clusters and their characteristics.


[1] Anzahl der Stromnetzbetreiber in Deutschland in den Jahren 2012 bis 2022. Hamburg: Statista, 2023.

[2] Länge des Stromnetzes in Deutschland nach Spannungsebene im Jahresvergleich 2010 und 2021. Hamburg: Statista, 2023

[3] Köppl, Simon; Samweber, Florian; Bruckmeier, Andreas; Böing, Felix; Hinterstocker, Michael; Kleinertz, Britta; Konetschny, Claudia; Müller, Mathias; Schmid, Tobias; Zeiselmair, Andreas: Projekt MONA 2030: Grundlage für die Bewertung von Netzoptimierenden Maßnahmen – Teilbericht Basisdaten. München: Forschungsstelle für Energiewirtschaft e.V. (FfE), 2017

[4] Wintzek, Patrick; Shawki Alsayed, Ali; Monscheidt, Julian; Gemsjäger, Ben; Slupinski, Adam; Zdrallek, Markus (Bergischen Universität WuppertalSiemens AG, 2021, BUW-01 21 )

[5] Gust, Gunther: Analyse von Niederspannungsnetzen und Entwicklung von Referenznetzen – Masterarbeit an der Fakultät für Wirtschaftswissenschaften. Karlsruhe: Karlsruher Institut für Technologie (KIT), 2014

[6] Eisenreich, Marc: Einbindung dezentraler Erzeuger am Beispiel von Photovoltaikanlagen ins elektrische Verteilungsnetz und die Auswirkungen auf die Netzstruktur. Darmstadt: Technische Universität Darmstadt, 2018.

[7] Kerber, Georg: Aufnahmefähigkeit von Niederspannungsverteilnetzen für die Einspeisung aus Photovoltaikkleinanlagen. München: Technische Universität München, 2011.

[8] Meinecke, Steffen; Drauz, Simon; Klettke, Annika; Sarajlić, Džanan (Universität Kassel Institut für Energiemanagement und Betrieb elektrischer Netze, 2020-01-13, UK-01 20 )

[9] Scheffler, Jörg: Bestimmung der maximal zulässigen Netzanschlussleistung photovoltaischer Energiewandlungsanlagen in Wohnsiedlungsgebieten. Chemnitz: Technische Universität Chemnitz, 2002.