Series of articles on the characterisation of low-voltage grids: Characterisation of low-voltage grids

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

The characteristics of individual low-voltage grids (LV grids) are shaped by various factors which differ significantly from one grid to another. In order to typify the German LV grids, geographical, infrastructural and socio-demographic aspects can thus be used as distinguishing indicators in addition to the energy technology parameters that ultimately define the grids. In various studies, these factors have already been investigated and evaluated in order to characterise the LV grid for different regions. Within the framework of a meta-analysis, these studies were analysed and compared in order to work out their commonalities, but also their differences. The analysis shows a very diverse set of studies, whereby the processes and relevant parameters were in many cases only superficially defined or described. From a selection of seven studies with a sufficiently well-founded information base, parameters were identified that are suitable for characterising LV grids. Figure 1 lists the main criteria that have been used in the literature to typify clusters and ultimately LV grids.

Figure 1: Studies describing low-voltage grids and parameters they used

The table illustrates that there is no clear consensus in the literature regarding the parameters relevant for the clustering of LV grids. However, it must be taken into account that the selection of parameters in the studies is defined on the one hand by the underlying methodological clustering approaches and on the other hand there are also correlations between the parameters, which means that a clear differentiation is not possible. In order to verify the relevance of the respective parameters, the results of the literature were compared in detail and subsequently verified by own investigations with a data set of 1,200 real LV grids. The most relevant parameters in the literature are discussed below.

Characterizing parameters of LV grids

Distance to the nearest neighbour: The distance between the buildings of an LV grid reflects the compactness/densification of a supply area. In urban regions, the value tends to be lower than in rural regions, as the area is more densely populated and the distances between the buildings and the lines of the supply networks are therefore shorter. Very similar to this parameter is the average cable distance (length of all cables in the LV network divided by the number of grid connection points (GCP)) of the grid. The length of the physical cable between the buildings (without considering stub lines to the buildings) is roughly equal to the geographical house distance, which means that the network length and the number of GCPs can ultimately be used to calculate an indicator of the settlement structure of the supply area. The close link between electrical and geographical parameters is particularly evident here.

Population density/number of apartments: The population density is a measure of the degree of urbanisation of the respective network area. The population density ultimately allows conclusions to be drawn about two essential parameters: firstly, the compactness of the settlement (cf. distance between houses and the nearest neighbour) and secondly, the number of residents per building. The number of residents per building correlates with the number of apartments per building, which in turn correlates with the height of the buildings. For example, inner‑city districts have a high population density, as well as a high number of apartment buildings (MFH), which, depending on the type of development (e.g. row development), also have a high degree of compactness. The number of residential units is determined by the grid operator via the number of electricity meters, whereby commercial units and special consumption facilities also have their own meters. The number of apartments per building in combination with the parameter “house distance to the nearest neighbour” thus already provides a clear indication of the characteristics of the cubature. The combination thus makes it possible to distinguish urban from rural LV grid areas.

Number of grid connection Points: The number of GCPs per grid area supplied by a local grid transformer (LGT) is a parameter that cannot be derived without knowledge of the actual grid plans. This parameter correlates with parameters of the settlement structure, whereby rural/suburban regions with smaller buildings have a higher number of GCP per grid in contrast to urban regions with large buildings. However, the number of GCPs per grid area is also influenced by the individual supply task. Grid areas whose supply area has a higher commercial share tend to have a significantly lower number of GCPs than those with a focus on supplying private households.

Transformer rating: The rating of the transformer that supplies a grid area is also correlated to the settlement structure and the supply task. The more buildings or end consumers are connected to an LGT or the more energy-intensive their consumption profile, the higher the rated power of the transformer. To investigate the influence of the type of building on the transformer rating, independently of the number of buildings or GCP in the grid, the transformer rating was often normalised to the number of GCP in the literature. It is also shown that there is also a correlation between transformer rating and the proportion of buildings in the commercial and service sector (CS units). LV grids with a high proportion of commercial buildings generally have a relatively high transformer rating per GCP.

Grid lines: The parameter grid lines include a number of parameters in the literature, such as the number of circuits originating from the LGT, the maximum line length per circuit, the associated impedance, and the average line length. The commonality of these attributes is that they describe the dimensions of the topology and its topography. In the literature, these parameters are classified as less characteristic, as they are ultimately shaped by the characteristics of the settlement structure and show strong fluctuations even in similar grid areas. The conclusion on the settlement structure is only meaningful from the line lengths if further parameters, such as the characteristic supply task of the region, are known.

In addition to the described parameters, several other features can characterise an LV grid and correlate with the described parameters. From the examination of the intersection of parameters in the literature, it appears that LV grids can essentially be characterised by the primary parameters “transformer apparent power per GCP”, “distance to nearest neighbour” and “number of apartments per GCP”, as these define the settlement structure with sufficient accuracy. In the following contribution to the series, the identification of network clusters at LV level with the three identified parameters is described and profiles of the identified clusters are presented.



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