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Potentials of wind power in Lusatia

A GIS-based, multi-criteria suitability analysis as decision support for new wind turbine locations under the aspect of nature conservation in Lusatia

Published onOct 05, 2022
Potentials of wind power in Lusatia

1. Introduction

1.1 Problem definition

“God created Lusatia, but the devil created the coal underneath.”

Sorbian proverb

Extreme weather events such as floods in western Germany and droughts in West Africa, which can be attributed to climate change, but also the new movement around Greta Thunberg are fueling the discussion about the need for an energy turnaround. With the declaration of the Paris Climate Agreement, Germany has committed itself to contribute to limiting the global temperature increase to well below 2°C, if possible to 1.5°C (BMWI 2021).

Although Germany is a pioneer in Europe when it comes to wind energy. About 27 % of the total energy produced in Germany comes from wind energy. In Brandenburg, the share of renewable energies in final energy consumption is to be 40 % in 2030, which was already defined in 2012 in the Brandenburg Energy Strategy (cf. MWAE 2012:23). In addition, greenhouse gas emissions are to be reduced by 75 % by 2030 compared to 1990 (ibid).

The expansion varies greatly within the country's borders. In addition to the city states, the state of Saxony brings up the rear (cf. Fraunhofer IEE 2018). Last year, just twelve new turbines with a total capacity of 42 MW were installed there (cf. MDR 2020). An important reason for the slow expansion of wind energy is, among other things, the lack of acceptance among the population. Therefore, a number of citizens' initiatives have been formed to advocate further expansion. The reservations are primarily directed against noise, light and visual pollution. Species and habitat protection also play a role (MDR 2020). But there are not only voices against this new form of energy generation. For example, awareness of climate change and nature conservation is growing and a movement against coal mining is developing.

1.2 Research objective and research questions

In order to address this complex of issues, an analysis of the status quo of the current coal and wind energy infrastructure will first be conducted. The aim of this first analysis is the geographic processing of coal deposits, power plant sites as well as active and abandoned opencast lignite mines for the reference year 2020. Furthermore, the spatial distribution of the already existing wind power plants and their power shall be presented. The research question (RQ1) is:

RQ1: How much electricity is produced from a) coal and b) wind in the reference year 2020 in the Lusatia region?

The main part of the work forms a multi-criteria potential analysis, which aims to identify possible municipalities for wind power plants. A special feature is the consideration of an area dominated throughout by fossil fuels. From this, the following, second research question (RQ2) can be derived:

RQ2: To what extent are communities in the Lusatia region suitable for electricity access from wind energy against the background of the preservation of nature conservation areas, due to their spatial structural and energy-specific characteristics?

Based on the potential analysis, three scenarios will be derived. The scenarios should cover the spectrum optimistic – moderate - pessimistic. For this purpose, key indicators such as electricity consumption, wind, conservation and land cover data are selected and their values adjusted for the various scenarios. The reference year is 2035, because recent calculations assume that the 1.5 degree target will be reached as early as 2030. Added to this is a transition period of five years for the construction of new wind turbines. In addition, Germany will phase out coal-fired power generation by 2038 at the latest, and preferably as early as 2035 (cf. BMU 2021). The third research question (RQ3) is:

RQ3: How much area is available for potential wind power plants in Lusatia in the reference year 2035?

2. Characterization of the study area and status quo of nature conservation

The region of Lusatia, which includes Lower Lusatia as well as Upper Lusatia (hereafter: Lusatia) with a total of 239 municipalities, is belonging to the federal states of Brandenburg and Saxony (cf. Fig 1). The economic region of Lusatia, which adjoins Berlin to the south, is a cooperative association of the Brandenburg districts of Dahme-Spreewald, Spree-Neiße, Oberspreewald-Lausitz, Elbe-Elster and the independent city of Cottbus, as well as the Saxon districts of Bautzen and Görlitz. The study region is home to 1.165.246 inhabitants.

Fig. 1: Representation of the study area, Source: own illustration, based on © GeoBasis-DE / BKG 2020.

With the exception of the cities of Bautzen, Cottbus, Görlitz, Finsterwalde and Hoyerswerda, the region is predominantly rural. This includes, among other things, a low settlement and population density as well as a high proportion of land used for agriculture and forestry. Furthermore, numerous nature reserves can be identified. Fig. 2 show the spatial extent of nature reserves, nature parks, FFH areas, biosphere reserves, landscape conservation areas, national parks and bird sanctuaries.

One of the most famous landscapes is the Spreewald, where man has created a cultural landscape over centuries that is unique in Europe. More than 100 pairs of white storks have been counted. White-tailed eagles and ospreys are found, as well as cranes, black storks, red kites and buzzards. Due to the water labyrinth, the wet meadows, floodplain forests, a distinctive flora could develop. The biosphere reserve, which has been recognized by Unesco since 1991, is home to 585 red-listed plant species, including the iris, orchids and cuckooflower (cf. MLUK 2019:72).

The Upper Lusatian Heath and Pond Landscape extends in the middle of the study area. It is one of the most species-rich regions in Germany. The region is a resting area for numerous migratory birds and home for many, partly endangered animal and plant species, such as white-tailed eagles, cranes, kingfishers, otters or the bell heath (ibid).

Another example is the Schlaubetal, which partially extends into the study area. It is home to numerous species on the wet meadows, where orchids grow and almost 700 butterfly species have been recorded. The landscape types - bogs, meadows, inland dunes - have been preserved in their original state (MLUK 2019:56).

The numerous FFH areas should not remain unmentioned, such as the Friedländer Valley, the meadow and pond landscapes around Peitz, Calau, Altdöbern, the Spree lowlands near Bautzen, the Elster lowlands and western Upper Lusatia between Senftenberg and Ortrand as well as the Königshainer Mountains east of Görlitz.

Fig. 2: Areas of nature conservation, source: own illustration, based on © SMUL (2021) and © LGB (2021)

In Lusatia, there exist two active opencast mines in Brandenburg: Jänschwalde and Welzow Süd. In the Saxon part there are the opencast mines Nochten and Reichwalde (cf. Fig. 3). The two Brandenburg opencast mines alone produce around 30 million tons of lignite per year. 10 million metric tons of lignite alone are mined annually in the Jänschwalde open pit mine, which is used exclusively to supply fuel for the Jänschwalde power plant. In the Lusatian region as a whole, around 60 million tons are produced from the four opencast mines mentioned above (cf. MWAE n. y.). The mined lignite is delivered to the opencast mining sites and processed at the power plants in Brottewitz (Mühlberg/Elbe), which has a capacity of 26 MW; Boxberg (2.575 MW), Jänschwalde (Teichland-Neuendorf, 3.000 MW) and Schwarze Pumpe (Spremberg, 1.600 MW) (cf. Staatskanzlei Brandenburg 2021).

Fig. 3: Spatial distribution of open cast lignite mines and power plants, Source: Own illustration, based on © ESRI (2020), © LGB (2021) and © SMUL (2021)

3. Methodology

The work is divided, according to the research questions, into 1. an inventory analysis, 2. into a multi-criteria potential analysis, whereby methods of advanced geoinformatics are used and 3. the derivation of three possible scenarios (cf. fig. 4). The detailed description of the inventory analysis is omitted here, because the results have been integrated in chapter 2.

Fig. 4: Illustration of the methodology in a flow chart, Source: own illustration

3.1 Multi-criteria potential analysis

The study region is to be methodically analyzed in five categories with the help of a multi-criteria potential analysis. For each category, justified indicators were selected, which are subsequently normalized, weighted and summed. The data preparation and calculation takes place in QGIS. The potential calculated for each municipality is finally visualized in a potential map. The selection of criteria took the form of an iterative research process and was guided by the scientific embedding as well as by the availability of data, the time reference and the spatial reference.

  • Upper category 1: Settlement and spatial structure: Population density [EW/km²], Trade tax [EUR/inhabitant], Average slope [1 arcsec], Proportion of area 1.000 m away from settlements [%],

  • Upper category 2: Nature conservation: Proportion of area 1.000 m away from conservation areas [%], Share of nature reserves per municipality [%]

  • Upper category 3: Energy infrastructure: Total electricity consumption (residential, commercial, industrial) [MWh/year]

  • Upper category 4: Fossil Fuels: Share of coalfired electricity produced in total electricity consumption [MW], Coal production value [MW]

  • Upper category 5: Wind energy: Average wind speed 100 m height earth surface [m/s], Average Wind Power Densitiy [W/m²],Electricity produced from wind power plants [MW], Share of wind energy produced in total electricity consumption [MW]

Once all the data have been selected, aggregated to the municipal level and normed, the next step is to calculate the weighting factors (WF). Since there are no suitable studies from which to reference weighting factors, these had to be calculated separately. This is done using a utility analysis in which each criterion is compared to each other. On a point scale of 0-10, their importance is subjectively assessed. 10 points are awarded if an alternative fulfills the criterion "outstandingly" or is of particularly high importance. 0 points mean no relevance. The higher the score, the more influence a criterion has. The same number of points is awarded if both criteria have identical importance (cf. BDI 2021). The points were awarded in the form of a group discussion in which the group members discussed and estimated the importance of the individual criteria. The results are presented in the form of a pair comparison matrix (see tab. 1).

Tab. 1: Determination of the weighting factors (WF) with the use of a utility analysis with a 0-10 rating scale, Source: own illustration

3.2 Scenarios

3.2.1 Technical background information about wind turbines

A large number of different types of wind turbines with different characteristics exist. For this report, the VESTAS V90-2.0 MW model is chosen as a reference model, which has a hub height of about 80 m and a rotor diameter of 90 m (cf. VESTAS 2021). This type is the most widely used wind turbine in Lusatia. The closest wind speed data corresponding to the requirements of the turbine model are available at 100 m height. A wind speed of 5.3 m/s at 100 m height is the minimum value for the assumption of low wind turbines (cf. Bovet et al. 2015) and 4 m/s for our model (cf. VESTAS 2021). In Lusatia, this value is reached everywhere and, accordingly, a minimum wind speed of 6.5m/s is assumed. The reference model reaches its highest performance around this value. The slope must be less than 30°, because only then is it possible to build wind turbines (Bovet et al. 2015).

3.2.2 Description of the Scenarios

Three scenarios will be derived for energy production with wind turbines with a focus on nature conservation in order to identify potential areas for wind turbines. Nevertheless, the focus for the scenarios is more on spatial modeling methods than on realistic development and implementation of the results. The complexity of the physical and social conditions and their interactions necessary to install wind turbines is beyond the scope of this report. Therefore, for simplification, the following preliminary assumptions are made:

  1. Lusatia is considered a closed region, with all generated energy consumed within the area. Similarly, electricity imports and exports are not included.

  2. Demographic movements, such as migration and domestic migration processes, are not considered.

  3. The settlement dataset was simplified in that no distinction is made between different types of settlements, e.g. residential areas, commercial areas and industrial areas, but settlements are considered as a single group.

  4. The different types of land use do not change over time.

Red Scenario: In this scenario, environmental and climate issues are not a priority, and the need for sustainable energy takes a back seat. Energy consumption will increase slightly and fossil fuels, especially coal, will continue to be used. However, the share of fossil fuels in the total electricity mix decreases. The share of sustainable energy, and thus also wind energy, will be increased to a small extent to 40%. Wind turbines must maintain a minimum distance of 1000 m from settlements (cf. Fachagentur Windenergie 2021). This specific distance is set by a new law, but is not necessarily based on scientific studies (cf. Hartmann 2021). The following distances in the other scenarios are based on this figure. Additional wind turbines can be erected in the immediate vicinity of nature conservation areas, even within Natura2000 and FFH areas, as is already possible today (cf. LAG VSW 2015). They can also be located in forests, groves and open spaces if they are not protected areas, despite the exceptions mentioned above.

Green scenario: The second scenario envisages the most stringent energy-saving measures and the greatest consideration for the environment. Energy consumption will be slightly reduced and fossil fuel consumption will be greatly reduced, and coal-fired power plants will be eliminated as an energy source. The minimum distance from settlements will be 500 m, an estimated average of several regulations. On the other hand, a distance of 1000 m from protected areas will be set. The value is based on studies by NABU on how wind turbines can disturb bird habitats, for example. NABU found that various bird species avoid proximity to turbines and recommends a minimum distance of 1000 m from breeding areas (cf. LAG VSW 2015). Only open space is considered as a potential area for wind turbines to minimize the risk of destruction of important habitats. This explains why the second scenario uses less energy than the third and the share of wind power is 50 %. One could instead focus more on photovoltaics or other alternatives, such as hydrogen.

Yellow scenario: The last scenario is a moderate scenario. It focuses on technical inventions and assumes that there will be more efficient turbines that operate at lower wind density and wind speed, although they are more efficient. Therefore, wind power has the highest share at 60 %. Communities must also be financially able to afford the turbines. Energy consumption remains the same as today, with most energy coming from sustainable sources and all open-pit coal. mines being closed. The scenario is only moderately considerate of the environment. The minimum distance to settlements will be 750 m and to nature reserves 300 m. The data sets for the different scenarios are prepared in the same way. Only different variables are adjusted, resulting in the respective scenario. There are seven variables in total, five of them which will not change in the future (see tab. 2, green frame). The variables framed in yellow are energy-related, with production and consumption adjusted to the scenario. All calculations are performed in QGIS unless specifically stated otherwise.

Tab. 2: Input data for the corresponding scenarios for the year 2035, Source: own illustration

3.2.3 Compute scenarios

At first, the prepared vector data sets are unionized and dissolved. The result represents areas where it is possible to install wind turbines. Of all the different vector layers an intersection is made, so only the area which is covered by all layers is extracted. The resulting area represents potential locations suitable for wind turbines (hereafter: PWT). Finally, the future energy production and consumption is pointed out. The different energy production levels for the particular scenarios coming from benchmarks in 2020 are calculated. In 2020, 17 % of the produced energy is generated through wind energy. The same year about 10 GWh (9.852.431 MWh) were consumed in Lusatia.

First, the energy produced by the wind turbines is calculated in R. The power P is indicated for each type of wind turbine.

E = P * t (E Energy, P Power, t time)

The energy consumption and production is given in Energy/time. The calculation below shows the units.

MWh/year = MW * hyear / year (with hyear= 24 h/d * 365 d/y = 8760 h/y)

The energy for our model turbine (EWT) VESTAS V90-2.0 MW (produced in one year):

EWT = 2 MW * 8760 h/year = 17520 MWh/year

For the third model, an assumption is made, that a more efficient wind turbine is used with power of 3 MW.

EWT = 3 MW * 8760 h/year = 26280 MWh/year

The share of energy produced by wind has to be distributed over the PWT of each scenario. The result is an assumption about the number of wind turbines that have to be installed to fulfill the energy need. The energy consumption gest adapted.

ESC= E2020 * ECSC

(with ESC = energy consumed in 2035, E2020 = energy consumed in 2020 and ECSC = energy production)

Every single polygon has its own size and ESC is evenly distributed over the polygons. These values are transformed into the amount of wind turbines needed in each area.


(with NWT = Number of wind turbines, ASC = Area share of polygon on amount of whole scenario and EWT = Energy produced by wind turbine)

4. Results

4.1 Multi-criteria potential analysis

Fig. 5 shows the results of the potential analysis. There are regions with a high to very high potential. This concerns the center of the study region with the municipalities of Großräschen, Lichterfelde-Schacksdorf, Welzow, Spremberg, Drebkau and Hoyerswerda; the north as well as the northwest, which includes the cities and municipalities around Herzberg and Falkenberg/Elster, Golßen/Spreewald as well as the southeast of the region with the cities and municipalities of Görlitz, Löbau, Herrnhut and Ebersbach-Neugersdorf. It is noticeable that in the center of the study region, in the southeast, and in Jänschwalde and the surrounding area, i.e. in the vicinity of the high potential areas, active and abandoned opencast mines can also be found. On the other hand, a rather low potential was calculated for the west and southwest of Lusatia. The municipalities in the Spreewald and south of Boxberg and north of Cottbus and Peitz also have a very low potential. From the total potential, Cottbus emerges as the first-placed city, followed by Görlitz, Schipkau, Großräschen and Welzow, Ebersbach-Neugersdorf, Schönwald and Bautzen. The last ranked municipalities are Heideblick, Oybin, Schenkendöbern, Calau, Krauschwitz, Jonsdorf, Lohsa, Plessa, Sohland a. d. Spree Burg/Spreewald, Lieberose and Byhleguhre.

Fig. 5: Total potential by summation of the five upper categories, Source: own illustration, based on the data and calculation basis and on © GeoBasis-DE / BKG 2020

4.2 Results of the scenarios

The results of the scenarios are presented in three maps (Fig. 6-8). For the most optimistic scenario, where, among other things, strict nature conservation rules and a wind energy share of 50 % are predicted, potential wind turbines have 1.392 km² of land available (Fig. 7). For the pessimistic scenario, a potential area share of 2.478 km² remains in entire Lusatia (Fig. 6). In the moderate scenario (Fig. 8), only 1.364 km2 area remains.

Fig. 6: Results of the red scenario, the most pessimistic, Source: own illustration

Fig. 7: Results of the green scenario, the most optimistic, Source: own illustration

Fig. 8: Results of the yellow scenario, the moderate one, Source: own illustration

5. Discussion and Uncertainities

The areas with high potential for wind turbines are mainly located in the center of the model region and on the northern, southern and western corners. This results partly from the indicators of settlement and spatial structure, as there is a higher concentration of population in the center, which means that the municipalities have a higher demand for wind energy. In addition, in all potential communities, the proportion of land located 1.000 m away from nature reserves and settlements is much higher.

All coal-fired power plants are to be shut down by 2038 at the latest. One result of the analysis includes communities where active and closed opencast mines are located. How could these areas be used for wind power in the future? There would be sufficient space on former opencast mines. Likewise, the distances to nature reserves and settlements are large enough. At the same time, slightly higher wind speeds can be identified. Post-mining landscapes are being considered as sites for wind turbines, not least because there are significantly fewer acceptance problems for these locations, since neither intact nature nor proximity to settlements is claimed, says Dr. Gerd Lippold, State Secretary for Energy, Climate Protection, Environment and Agriculture (cf. MDR aktuell 2021).

One example leads the way. We are talking about the open pit mine Vereinigtes Schleenhain in the south of Leipzig. A dozen wind turbines are scattered across the area. About 1.000 of them would be needed to replace the coal-fired power plant. Not all of them would have room on the land. From a construction point of view, it would be possible to install wind power. However, extensive geotechnical stabilization measures would be required. Although they could be suitable for wind power, some of these areas are difficult to develop as potential sites. The areas belong to the mining law, which presents further obstacles in terms of planning law than, for example, the development of available open areas. Politicians are called upon to act quickly and take action to remove these obstacles. The example from Leipzig could also be implemented for Lusatia. As stated in the second chapter, just 0,14 % of the Saxony's region is made available for the construction of wind turbines (cf. Bundesverband Windenergie 2021) and also Brandenburg has just around 30 designated areas (ibid). According to the areas of fitness suggested by both governments, our potential areas are located approximately in similar areas, avoiding areas of nature conservation and closed settlements.

6. Summary

Accordingly, this work focused on both nature conservation and wind energy. The aim was to identify communities in the Lausitz study region for potentially possible wind power plants and to develop three scenarios for the reference year 2035, in which concrete areas are available for this purpose.

RQ1: In 2020, the total production in Lusatia was 7.201 MW from coal. This electricity is produced by the power plants Brottewitz (Mühlberg/Elbe), which has a capacity of 26 MW, Boxberg (2.575 MW), Jänschwalde (Teichland-Neuendorf, 3.000 MW) and Schwarze Pumpe (Spremberg, 1.600 MW). 1.304 wind power plants are producing in total 3.034 MW in the study region.

RQ2: The final summation of all three upper categories shows that, against the background of nature conservation in Lusatia, three larger, coherent regions could be identified which are particularly suitable for possible new wind power plants.

  1. the cities and municipalities in the center of Lusatia (Cottbus, Jänschwalde, Welzow, Spremberg) and

  2. the cities and municipalities around Herberg and Falkenberg/Elster due to the landscape shaped by mining and its subsequent use of former opencast mines for wind power plants;

  3. the cities and municipalities in the southeast (Görlitz, Löbau, Herrnhut) primarily due to the lack of larger, contiguous conservation

RQ3: For the year 2035, 2.478 km² are available for wind power plants in Lusatia, provided that electricity consumption increases by 5 %, wind power may be erected in FFH areas and the wind power share is only 40 %. 1.397 km² remain in the optimistic scenario, provided that nature conservation guidelines are strict, the wind share is 50 %, and total electricity consumption decreases by 5 %. For the moderate scenario, 1.364 km² remain. Electricity consumption is identical to today and the share of wind power increases to 60 %.

The expansion of wind energy is undoubtedly a challenge for the coming decades against the background of climate change as well as resulting damage to humans and nature. The tightrope walk between the expansion of wind power is not without impact on flora and fauna and affects birds in particular, e.g. through collision, avoidance behavior and an associated loss of habitat (breeding and feeding habitats). The realization of future wind power plants in Lusatia must therefore be carried out in harmony with nature without exceptions.


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