“right” people together
3.3 Expanding renewable energy within the Alpine ecological network
The Alpine ecosystems have delivered living space, food, and energy to their populations for millennia (Yamagata et al., 2010). Nowadays, a diversification of renewable energy (RE) production is taking place. Tra-ditional RE technologies, such as bioenergy and hydro-power, are seen as only one part of the broad energy portfolio in the Alps and are now inter-alia comple-mented by wind power, solar, and geothermal energy.
However, the expansion of all these technologies in
competition with other land uses may increase land-scape fragmentation (Svadlenak-Gomez et al., 2013). If a functional ecological continuum is not ensured in the Alpine landscapes, their biodiversity and the provision of ecosystem services for the local populations may be threatened. Despite the general public support for RE expansion, such sustainability concerns can reduce public acceptance in certain locations. Proper spatial planning of RE expansion should consider ecosystem
The Roselend Dam is located in the Savoie department in the French Alps. Its construction was completed in 1962 for the primary purpose of hydroelectric power generation, and it supports the 546 MW La Bâthie Power Station.
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connectivity so that environmental benefits from green energy production are not neutralised by its potential environmental impacts (Füreder and Kastlunger, 2011).
The traditional tool to conserve biodiversity from hu-man activities has been the creation of strict protected areas (PAs) such as national parks and nature reserves (UNEP-WCMC, 2014). However, functional ecosystems and threatened species populations cannot be main-tained if PAs are fragmented within the landscape (Dudley, 2008). In spite of this potential fragmentation, there are conservation strategies, such as the Natura 2000 network, which aim to increase the ecological connectivity between biodiversity Pas (EEA, 2014).
On the other hand, the diversity of PAs also gives room for integration of nature conservation with sustainable RE development strategies (Svadlenak-Gomez et al., 2013). The Alps have a large variety of PAs that fall un-der different categories and classifications. Different RE systems can be more or less sustainable with respect to their impact on the ecosystems and their services. Thus, an RE technology could be suitable in protection cate-gories allowing for sustainable use of natural resources but at the same time incompatible with stricter catego-ries. The potential for RE energy in the Alpine region will depend on the protection constraints determined by the network of PAs. Furthermore, the mountainous topography of the Alps, that is accessibility, adds to the complexities involved in planning a system balanced between RE production and environmental protection.
Social factors, infrastructure requirements, economic
constraints and environmental parameters have to be considered and integrated into a sustainable system.
Thus, a spatial approach is needed to address these is-sues in a comprehensive way.
Researchers at the International Institute for Applied Systems Analysis (IIASA) and the Mercator Research In-stitute on Global Commons and Climate Change (MCC), jointly with colleagues from the Alpine Space Project recharge.green developed a decision support system (DSS) for the entire Alpine region, aiming at quantify-ing RE potentials balanced with the protection of na-ture and ecosystem services. The underlying scenarios for the DSS are based on a comparative GIS approach identifying and aggregating the large set of PAs, as well as their suitability for the different RE types. To assess the different local RE potentials and impacts, a harmo-nisation methodology has been developed based on the International Union for Conservation of Nature’s (IUCN) System of Protected Areas, with different sce-narios depending on the protection constraints. A low protection scenario represents the fragmentation of PAs without considering ecological connectivity networks.
A high protection scenario puts emphasis on inter-con-necting protected landscapes to maintain a functional ecological continuum. This scenario, which includes the Natura 2000 network and additional buffer zones in strictest PAs, assumes increasing protection constraints in all PAs.
Figure 6 shows the harmonisation results, where the low protection scenario allows two-thirds of the Alpine area to be used without constraints for RE production, while only three percent is incompatible with RE pro-duction. The high protection scenario only features half of the Alpine space as unconstrained, while the other half is incompatible or only marginally compatible with RE production (Serrano León, 2015).
Thus, there are considerable trade-offs between nature protection and the potential for RE production. The available area and the potential for RE production can be notably reduced by higher conservation demand, which could be enhanced by the additional buffer restrictions of the strictest protection categories, or through the exclusion of the Natura 2000 network for RE production.
In a next step, the techno-economic engineering model BeWhere (Schmidt et al., 2011; Leduc et al., 2012) has been applied to carry out the spatial optimisation of the Alpine RE potentials for bioenergy, hydropower, wind Excursion to the Pilot Region Berchtesgaden/Salzburg.
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power and solar energy. BeWhere models the entire sup-ply chain of an energy technology, its costs and carbon emissions. The optimal location of green field plants and their capacities can be identified based on a detailed supply and demand assessment, thereby determining the optimal RE mix for the region in different scenarios (Leduc et al., 2015a). Each of the four RE technologies can be assessed in isolation, but also in the presence of each other, thus taking into account competition between them. Based on the harmonisation results for protection categories explained earlier, Figure 7 visu-alises scenario results from BeWhere for the four RE technologies. In particular, the optimal production loca-tions and plant capacities for each RE technology are displayed. The results reveal substantial differences with respect to suitable locations, but also the changing focus areas under different assumptions in low protection and high protection scenarios (Kraxner et al., 2015a).
The results of the harmonisation approach are fi-nally fed into the Decision Support System (DSS) visualising results online and making them publicly accessible through an inter-active user interface on the Joint Ecological Continuum Analysing and Map-ping Initiative (JECAMI). This online application tar-gets a variety of stakeholders such as energy experts, technical contractors, locals and also policymakers from local administrations interested in future RE options for the Alps (Figure 8, Leduc et al., 2015b).
Stakeholders can interactively access over 100 dif-ferent scenarios for optimal RE production bal-anced with ecosystem services protection depend-ing on their preferences and needs. The geographi-cally explicit visualisation enables stakeholders to get a first-glance understanding of their region of interest.
// Figure 6: Harmonisation of environmental protection areas
Source: adapted from EEA 2014, UNEP-WCMC 2014
substantially more unconstrained and compatible areas for RE production than the high protection scenario (right). The compatibility categories are indicated by the color ramp in the legend, and compatibility shares of the total Alpine space are indicated in the pie charts.
Low Protection Scenario High Protection Scenario
0.6 %
23.5 % 19.7 %
67.3 %
2.8 % 52.6 %
9.7 % Compatibility classes 23.6 %
No restrictions (100 %) Compatible (90 %)
Moderately compatible (50 %) Moderately compatible (30 %) Marginally compatible (20 %) Marginally compatible (10 %) Incompatible (0 %)
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// Figure 7: Renewable potentials and plant locations for two set of scenarios *
Source: BeWhere, IIASA, 2015
* Small colored dots indicate the potential production sites and the legend indicates the capacities by colour.
Low Protection Scenario Bioenergy
Hydropower
Windpower
Solar energy
High Protection Scenario Bioenergy
Hydropower
Windpower
Solar energy 0.0 – 0.1
0.2 0.3 – 0.4
1 – 37 38 – 173 174 – 373
3 – 7 8 – 13 14 – 30
9 – 14 15 – 17 18 – 20
3 – 7 8 – 13 14 – 30 1 – 15 16 – 37 38 – 173 0.0 – 0.1 0.2 0.3 – 0.4
Hydropower stations S59 (TWh/a)
Wind mills S59 (TWh/a) Hydropower
stations S24 (TWh/a)
Wind mills S24 (TWh/a)
Solar plants S24 (TWh/a)
9 – 14 15 – 17 18 – 20 Solar plants
S59 (TWh/a)
High Medium Low Biomass
selected S24 (TWh/a)
Biomass selected S59 (TWh/a)
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The results of this new approach show considerable trade-offs between nature protection and the poten-tial for RE production, with significant differences depending on scenario assumptions. Available area and potential for RE production are notably reduced when higher restrictions are assumed (Kraxner et al., 2013). With the help of the DSS, RE potentials can be quantified under different conservation and
ecological connectivity scenarios (Kraxner et al., 2015b). Furthermore, it demonstrates the importance of clearly defining policy objectives in order to bal-ance protection and RE needs (recharge.green, 2015).
Increased coherence between PA definitions across national boundaries would provide an improved basis for ensuring the long-term sustainability of RE pro-duction in the Alpine space.
BeWhere model runs for 100+ scenarios, based on the harmonisation of protection area, displayed on JECAMI. The box on the left hand allows the user to interactively switch between the different RE technologies. Furthermore, the user can set different fossil fuel costs (reference scenario/subsidies to RE), the desired cost per ton of CO2, or switch between protection levels (high/low). The up-per screenshot shows optimal harvesting and production areas (yellow squares) of bioenergy under a very low subsidy rate (1.5 times higher fossil fuel costs). The lower screen shot shows the substantially increased area after increasing the subsidies (2.5 times the fossil fuel costs). Detailed energy production potentials, costs and emissions avoided can be read from the lower part of the settings box.
// Figure 8: Screen shots from the interactive DSS user interface on JECAMI
Source: BeWhere, IIASA, 2015, modified screenshots from JECAMI