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Wind power is a promising technology to reduce greenhouse gas emissions in the electricity sector. However, besides climatic limitations such as prevalent wind speeds, further parameters like population density, land use, and protected areas restrict the available sites. Typically, in the assessments of wind power potential, the restrictions are normatively chosen based on legal, technical, or other criteria. We assess in contrast wind power expansion in the Czech Republic considering wind power site characteristics observed in Austria and Denmark. For this purpose, we use spatially highly resolved data on wind turbine deployment in Austria and Denmark and join it with high quality input data from the LUISA terrestrial modelling platform, and the IRENA Global Wind Atlas. In preliminary calculations, we identified a maximum potential area of 769 km2 in the Austrian scenario and 519 km2 in the Danish scenario for the Czech Republic which translates to 3,685 MW respectively 913 MW of installed capacity. The results show, that the calculated wind power potential only partly meets the capacities as required by recent studies on the decarbonization of the electricity sector. This illustrates the existing challenge of a large-scale installation of onshore wind power turbines in densely populated European areas. A sensitivity analysis examined the impact of the single parameters in a maximum and minimum scenario. As expected, the availability was mainly determined by wind speed, the three land use forms urban areas, agriculture and forests, as well as the population density close to the wind power sites. Protected areas do not seem to significantly limit the potential areas for wind power expansion. The data sets generated in this study can be used in further research to identify and address land use conflicts arising from the expansion of renewable energies.

Die soziale Akzeptanz ist mehrdimensional und umfasst soziale, politische, rechtliche, ökologische, technische und ökonomische Faktoren, die sich auf drei Akzeptanzebenen wieder finden: a) Sozio-politische Akzeptanz der Technologien und politischen Handlungen durch die Öffentlichkeit, zentraler EntscheidungsträgerInnen bzw. Stakeholder und PolitikerInnen; b) Lokale Akzeptanz, die durch Fragen des Vertrauens und der Gerechtigkeit geprägt ist; c) Marktakzeptanz, bei der die maßgeblichen Akteure die Betreibergesellschaften, Interessensvertretungen, InvestorInnen und KonsumentInnen sind. Die soziale Akzeptanz kann sich im Zeitverlauf sowohl positiv als auch negativ verändern und ist abhängig von einem komplexen Zusammenspiel individueller Präferenzen und gesellschaftlicher Wertvorstellungen. Die Akzeptanzforschung beschäftigt sich daher mit der Identifikation von Gründen zur Annahme (Akzeptanz) und Ablehnung (Nicht-Akzeptanz) der Windkrafttechnik. Darüber hinaus werden im Bereich des Akzeptanzmanagements Handlungen und Vorgehensweise identifiziert, die die Anerkennung (Legitimität) der Prozesse und getroffenen Entscheidungen bei Windparkprojekten erhöhen. Im Folgenden zeigen wir die wichtigsten Ergebnisse aus dem Projekt TransWind auf und besprechen Rahmenbedingungen der Entwicklung der Windkraft in Österreich. Es werden Schlüsselfaktoren der sozialen Akzeptanz identifiziert und sowohl bestehende als auch neue innovative Verbesserungsmaßnahmen diskutiert.

TransWind assessed the key patterns of social acceptance of wind energy in Austria on the basis of a participatory integrated assessment including modelling and visualisation efforts. In order to ensure acceptance, decision-making processes have to be reformed, justice sustained and thereby both input and output legitimacy enhanced. All of these factors need to be taken into account when engaging stakeholders and civil society in decision-making processes about the future wind energy infrastructure in Austria.

Brazil’s hydropower generation, the major source of electricity generation, is subject to significant inter-annual variability. To reduce risks in the system and to increase power generation due to growing demand, it is necessary to promote other generation technologies, in particular from renewables. Especially in the North-East, wind power has high potential. To assess the influence of El Niño and La Niña cycles on and correlations of water inflows with wind power generation, a simulation model of the long-term wind power generation (1980-2016) in Brazil is developed. It is based on MERRA-2 reanalysis wind speed data and corrected with wind speeds measured by INMET and with wind power generation data from the homepage of ONS, and is spatially disaggregated to the level of states. Different interpolation, data cleaning, and bias-correction methods are tested, to find the best procedure for simulating wind power generation. Finally, impacts of El Niño and La Niña on annual wind power generation and correlations with water inflows are assessed. Results show that applying bias-correction using wind power generation data substantially improves the quality of the simulated time series. In contrast, wind speed bias-correction did not improve results in the South very much, but had a larger impact in the North-East. In most tested settings, the best results are obtained when Nearest Neighbour Interpolation is used with wind power bias correction. Results differ significantly between single states. Results with El Niño and La Niña indices are ambiguous: For several cases impacts after one to three months are found, for other after five to eight. El Niño shows a higher impact than La Niña or both together, whether positive or negative varies from region to region. Respecting these events can help in the prediction of future wind power generation. Water inflows show no significant correlation with wind power generation, when seasonality is removed from the timeseries., Datasets: https://doi.org/10.5281/zenodo.1470357