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The Design and Application of a Regional Management Model to Set Up Wind Farms and the Adaptation to Climate Change Effects—Case of La Coruña (Galicia, Northwest of Spain)

Blanca Valle, Javier Velázquez, Derya Gülçin, Fernando Herráez, Ali Uğur Özcan, Ana Hernando, Víctor Rincón (), Rui Alexandre Castanho and Kerim Çiçek
Additional contact information
Blanca Valle: Tragsatec, Calle Julián Camarillo, 6A, 28037 Madrid, Spain
Javier Velázquez: Catholic University of Ávila, Calle Canteros s/n, 05005 Ávila, Spain
Derya Gülçin: TEMSUS Research Group, Catholic University of Ávila, 05005 Ávila, Spain
Fernando Herráez: Catholic University of Ávila, Calle Canteros s/n, 05005 Ávila, Spain
Ali Uğur Özcan: TEMSUS Research Group, Catholic University of Ávila, 05005 Ávila, Spain
Ana Hernando: TEMSUS Research Group, Catholic University of Ávila, 05005 Ávila, Spain
Víctor Rincón: Department of Pharmacology, Pharmacognosy and Botany, Faculty of Pharmacy, University Complutense of Madrid, Plaza de Ramón y Cajal, s/n, 28040 Madrid, Spain
Rui Alexandre Castanho: TEMSUS Research Group, Catholic University of Ávila, 05005 Ávila, Spain
Kerim Çiçek: TEMSUS Research Group, Catholic University of Ávila, 05005 Ávila, Spain

Land, 2024, vol. 13, issue 12, 1-25

Abstract: The implantation of wind farms in the European territory is being deployed at an accelerated pace. In the proposed framework, the province of La Coruña in the autonomous community of Galicia is tested, with a wide deployment of this type of infrastructure in the territory initiated in the 80s, representing the third autonomous community with the largest exploitation of wind resources, which provides sufficient information, extrapolated to the entire community, to demonstrate the practical usefulness and potential of the method of obtaining the territorial model proposed in this article The regional has been used as the basic administrative subunit of the study variables, considering that the territory thus delimited could have common physical and cultural characteristics. The methodology presented in this article involves the collection and processing of public cartographic data on various factors most repeatedly or agreed upon in the consulted bibliography based on studies by experts in the technical, environmental, and environmental areas, including explanatory variables of risk in a broader context of climate change as the first contribution of this study. Another contribution is the inclusion in the model of the synergistic impact measured as the distance to wind farms in operation (21% of the total area of the sample) to which an area of influence of 4 times the rotor diameter of each of the wind turbines im-planted has been added as a legal and physical restriction. On a solid basis of selection of explanatory variables and with the help of Geographic Information Systems (GIS) and multi-criteria analysis (MCDM), techniques widely documented in the existing literature for the determination of optimal areas for the implementation of this type of infrastructure, a methodological proposal is presented for the development of a strategic, long-term territorial model, for the prioritization of acceptable areas for the implementation of wind farms, including forecasts of increased energy demand due to the effect of climate change and the population dynamics of the study region that may influence energy consumption. This article focuses on the use of multivariate clustering techniques and spatial analysis to identify priority areas for long-term sustainable wind energy projects. With the proposed strategic territorial model, it has been possible to demonstrate that it is not only capable of discriminating between three categories of acceptable areas for the implementation of wind farms, taking into account population and climate change forecasts, but also that it also locates areas that could require conservationist measures to protect new spaces or to recover the soil because they present high levels of risk due to natural or anthropic disasters considered. The results show acceptable areas for wind energy implementation, 23% of the total area of the sample, 3% conservation as ecological spaces to be preserved, and 7% recovery due to high-risk rates. The findings show that coastal regions generally show a more positive carrying capacity, likely due to less dense development or regulatory measures protecting these areas. In contrast, certain inland regions show more negative values, suggesting these areas might be experiencing higher ecological disturbance from construction activities. This information highlights the importance of strategic site analysis to balance energy production with conservation needs. The study provides insights into wind farm deployment that considers the visual and ecological characteristics of the landscape, promoting sustainability and community acceptance. For this reason, these insights can be effectively used for advancing renewable energy infrastructures within the European Union’s energy transition goals, particularly under the climate and energy objectives set for 2030.

Keywords: wind farms; carrying capacity; risk; climate change; management categories; priority areas (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
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