Solar Systems 2023

Methodology

The three maps each contain several layers covering different topics and areas. This is due to data protection considerations and academic reasons. The layers are self-contained; i.e. combining several of the two-dimensional layers will not generate any additional information.

More specifically, the maps consist of the following specialised layers:

Map 08.09.1 Photovoltaics contains 12 layers:

  • PV system locations for small systems up to 30 kWp (not true to location) and above 30 kWp
  • PV system locations – public sector
  • Installed capacity of the PV systems presented separately per borough and postal code area
  • Installed capacity of the PV systems per borough – public sector
  • PV electricity feed-in presented separately per borough and postal code area
  • PV potential (theoretical) – building and
  • PV potential (theoretical) – roof area
  • Relative coverage rate presented separately per borough (ratio of the output that can be achieved theoretically to the already installed capacity).

Map 08.09.2 Solar Thermal Energy contains 7 layers:

  • ST system locations (data protection reasons allowed only for a limited range of scales to be used for presentation)
  • ST system locations – public sector
  • Total number of ST systems presented separately per borough and postal code area
  • Total number of ST systems presented separately per borough – public sector
  • ST potential (theoretical) – building and
  • ST potential (theoretical) – roof area.

Map 08.09.3 Solar Potential – Irradiation contains 1 layer:

  • “Irradiation”.

Map 08.09.1 Photovoltaics

With the amendment of the Renewable Energy Sources Act (EEG) in August 2014, the responsibility for publishing PV system data was transferred to the Federal Network Agency (BNetzA) as a centralised institution with uniform standards across Germany. This is a distinctive feature of the current methodology. Previously, the responsibility for publishing PV system data was with the network operators, who would usually publish information on the address and generator output of all systems on their own websites. For data protection reasons, the Federal Network Agency only publishes the postal code for systems below 30 kWp; the exact address including street name and house number is only published for an output of 30 kWp or more.

Map layer “PV system locations for small systems up to 30 kWp (not true to location) and above 30 kWp”

The data set only includes systems that are subsidised according to the EEG. Systems that do not feed into the grid and use the electricity exclusively for self-supply are not included in the presentation. This applies for example to off-grid systems and stand-alone power systems, such as PV modules on parking meters, park lighting systems and in allotment gardens.

The location of systems above 30 kWp was determined based on the address details provided by the system data reported. It cannot be ruled out that these may deviate slightly from the actual system location in individual cases, as it was not always possible to match the system to its roof. Due to data protection regulations, systems of up to 30 kWp are not displayed at their exact location but are presented together in the centre of a specific postal code area.

The PV system data is based on preliminary reports from the core energy market data register of the Federal Network Agency. As data on existing systems is still being added, the figures are still incomplete. This data will be added successively as part of the updating process, however, i.e. the figures will be completed gradually.

Map layer “PV system locations – public sector”

This map layer shows the locations of PV systems on public sector buildings. These include buildings owned by the boroughs, buildings of the Berliner Immobilienmanagement GmbH (BIM) and buildings of Berlin’s public-law institutions. It also encompasses buildings owned by municipal housing associations and other affiliated companies of the State of Berlin. Not all companies and public-law institutions in which the State of Berlin has a stake have yet provided feedback on the expansion status of PV systems. The locations were identified by their exact address.

Map layers “Installed capacity of the PV systems per borough and postal code area”

The data set only includes systems that are subsidised according to the EEG. The Anlagenregisterverordnung (Installation Register Ordinance) (in force until August 2017) summarised all master and billing data for PV systems previously reported by the transmission system operators. This data is address-specific and was summed up per borough and postal code areas.

Map layer “Installed capacity of the PV systems per borough – public sector”
This map layer presents the number and installed capacity of PV systems on public buildings. The data was collected by exact address and aggregated at borough level.

Map layers “PV electricity feed-in per borough and postal code area”

The electricity feed-in data presented includes the billed quantities determined by the Stromnetz Berlin GmbH, aggregated by borough and postal code area. For the electricity feed-in, the measured data and the data billed in accordance with the valid, defined market processes is available. The available annual values are not to be regarded as final; changes may still have occurred in individual cases, for example due to billing corrections.

Considerable annual fluctuations in electricity feed-ins may occur in individual areas. Specific reasons may include weather fluctuations, system extensions or operational failures. Based on the available data, however, it is not possible to identify the exact underlying reasons.

Map layer “Theoretical PV potential per building”

The map layer shows the photovoltaic potential for the roof areas of Berlin’s buildings. In addition to the local global radiation, shading as well as the orientation and the angle of a roof area play a key role in the design of a photovoltaic system. Suitable roof areas were determined as part of an analysis of the potential. The irradiation conditions are illustrated by a colour scale on the map. These provide initial insight into the use of solar energy.

More detailed information for each building may be accessed using the factual data display. In addition to an assessment of how suitable a building is for the installation of a PV system, the installable capacity [kWp], the number of installable modules and the potential electricity yield per year [kWh/a] are listed. However, this information does not replace the expert assessment of the individual object that is still required in relation to other parameters, for example the statics of the roof, before a solar system may be planned in detail and eventually constructed. The technical suitability is therefore not guaranteed and needs to be determined for each individual case. Further information and advice (in German) are available from the SolarZentrum Berlin free of charge.

Existing data sources such as aerial photographs and ALKIS building floor plans, as well as a transparent calculation process, were used to determine the solar potential. More details may be found in the final documentation (IP SYSCON 2022, only in German). Only roof areas that have been found suitable are shown on the map. The suitability criteria selected included a “minimum available area of 7 m²” and the “achievement of a specific electricity yield of 650 kWh/kWp”. The map does not distinguish between roof areas that already have PV systems installed and those that do not, due to the data sources used. In addition, developments on buildings that were erected, modified, demolished or included in the Official Real Estate Cadastre Information System after the date of data collection (April 22, 2021) were not taken into account.

Map layer “Relative coverage rate of the actual output compared to the theoretical PV output that can be achieved by borough”

The theoretically achievable PV potential for Berlin’s rooftops was calculated in 2019 as part of the master plan study for the “Masterplan Solarcity Berlin” by the Fraunhofer Institute for Solar Energy Systems. The results were aggregated at borough level, and the relative coverage rates were determined from the ratio between the actually installed and the potential PV capacity.

At first glance, the coverage rates appear to be relatively low for the boroughs. However, the reasons for this lie in the deviation between theoretically calculated and technically achievable potential. This would have to be confirmed by further investigations and calculations in order to obtain an accurate picture.

Map 08.09.2 Solar Thermal Energy

At this point, it is helpful to remember that not every installed system could be recorded in the solar cadastre in its final version as of December 31, 2015. Six years and 468 new systems separate the location data of the cadastre and the updated and aggregated version from late 2021.

Map layer “ST system locations”

Due to data protection regulations, the presentation of system locations (as of December 31, 2015) is only permissible for certain scale ranges. The solar thermal systems are therefore presented only at a scale of 1:15,000 and larger.

Map layer “ST system locations – public sector”

This map layer shows the locations of ST systems on public sector buildings (as of March 31, 2023). These include buildings owned by the boroughs, buildings of the Berliner Immobilienmanagement GmbH (BIM) and buildings of Berlin’s public-law institutions. It also encompasses buildings owned by municipal housing associations and other affiliated companies of the State of Berlin. Not all companies and public-law institutions in which the State of Berlin has a stake have yet provided feedback on the expansion status of ST systems. The locations were identified by their exact address.

Map layers “Total number of ST systems presented separately per borough and postal code area”

The data presented also includes updates for the years between 2016 and 2022, i.e. additions based on information provided by the Federal Office of Economic Affairs and Export Control (BAFA). The data is only available at postal code level, which forms the most detailed level here. It was therefore possible to adjust the total number summed up at postal code and borough level. The location of individual systems, however, could not be identified.

Map layer “Total number of ST systems presented separately per borough – public sector”

This map layer presents the number and installed capacity of PV systems on public buildings as of March 31, 2023. The data was collected by exact address and aggregated at borough level. For comparison, the total number of solar thermal systems on public buildings is also indicated for the entire city of Berlin.

Map layer “Theoretical ST potential at building level”

The map layer shows the solar thermal potential for the roof areas of Berlin’s buildings. In addition to the local global radiation, shading as well as the orientation and the angle of a roof area play a key role in the design of a solar thermal system. Suitable roof areas were determined as part of an analysis of the potential. The irradiation conditions are illustrated by a colour scale on the map. These provide you with initial insight into the use of solar energy.

More detailed information for each building may be accessed using the factual data display. In addition to an assessment of how suitable a building is for the installation of a solar thermal system, the potential heat generation per year [kWh/a] is also indicated. However, this information does not replace the expert assessment of the individual object that is still required in relation to other parameters, for example the statics of the roof or required heat, before a solar system may be planned in detail and eventually constructed. The technical suitability is therefore not guaranteed and needs to be determined for each individual case. Further information and advice (in German) are available from the
SolarZentrum Berlin free of charge.

Existing data sources such as aerial photographs and ALKIS building floor plans, as well as a transparent calculation process, were used to determine the solar potential. More details may be found in the final documentation (IP SYSCON 2022, only in German). Only roof areas that have been found suitable are shown on the map. The suitability criteria selected included a “minimum available area of 4 m²” and the “achievement of a potential heat generation of 350 kWh/kWp per m²”. The map does not distinguish between roof areas that already have PV systems installed and those that do not, due to the data sources used. In addition, developments on buildings that were erected, modified, demolished or included in the Official Real Estate Cadastre Information System after the date of data collection (April 22, 2021) were not taken into account.

Map 08.09.3 Solar potential – Irradiation

Berlin’s calculation of irradiation includes all surfaces that may be found in the city, not only those of buildings and structural elements. It is therefore also suitable for evaluation purposes other than those required in the solar potential analysis. The method for creating the high-resolution grid data is described in detail in the final report on the solar potential analysis (IP SYSCON 2022) and will only be touched upon here briefly.

The analysis was based on aerial photography flight data of the year 2020 (SenStadtWohn 2020). A 3D model was derived from this data, which enabled, first and foremost, a three-dimensional analysis. This analysis was able to take into account the influence of the shading effect of trees, building structures and different positions of the sun, which may have a major impact, depending on the season. The monthly means of the long-term mean global radiation provided by the Deutscher Wetterdienst (DWD), here the mean between 1991 and 2020 (cf. Fig. 4), formed the basis for calibrating the calculation method.

In addition to the annual sums presented here, irradiation was also determined for the heating period between October 1 and April 30 in order to calculate the possible support towards heating that solar thermal energy may provide.