Wind Farm Siting Using a Spatial Analytic Hierarchy Process Approach: a Case Study of the Städteregion Aachen

FCN Working Paper No. 16/2014 Wind Farm Siting Using a Spatial Analytic Hierarchy Process Approach: A Case Study of the Städteregion Aachen Tim Höfer, Yasin Sunak, Hafiz Siddique and Reinhard Madlener November 2014 Institute for Future Energy Consumer Needs and Behavior (FCN) School of Business and Economics / E.ON ERC FCN Working Paper No. 16/2014 Wind Farm Siting Using a Spatial Analytic Hierarchy Process Approach: A Case Study of the Städteregion Aachen November 2014 Authors’ addresses: Tim Höfer RWTH Aachen University Templergraben 55 52056 Aachen, Germany E-mail: [email protected] Yasin Sunak, Reinhard Madlener Institute for Future Energy Consumer Needs and Behavior (FCN) School of Business and Economics / E.ON Energy Research Center RWTH Aachen University Mathieustrasse 10 52074 Aachen, Germany E-mail: [email protected], [email protected] Hafiz Siddique Institute for Power Generation and Storage Systems (PGS) Faculty of Electrical Engineering and Information Technology / E.ON Energy Research Center RWTH Aachen University Mathieustrasse 10 52074 Aachen, Germany E-mail: [email protected] Publisher: Prof. Dr. Reinhard Madlener Chair of Energy Economics and Management Director, Institute for Future Energy Consumer Needs and Behavior (FCN) E.ON Energy Research Center (E.ON ERC) RWTH Aachen University Mathieustrasse 10, 52074 Aachen, Germany Phone: +49 (0) 241-80 49820 Fax: +49 (0) 241-80 49829 Web: www.eonerc.rwth-aachen.de/fcn E-mail: [email protected] WIND FARM SITING USING A SPATIAL ANALYTIC HIERARCHY PROCESS APPROACH: A CASE STUDY OF THE STÄDTEREGION AACHEN T. Höfer1, Y. Sunak*,2, H. Siddique3, and R. Madlener2 1 RWTH Aachen University, Templergraben 55, 52056 Aachen, Germany 2 Institute for Future Energy Consumer Needs and Behavior (FCN), School of Business and Economics / E.ON Energy Research Center, RWTH Aachen University, Mathieustrasse 10, 52074 Aachen, Germany 3 Institute for Power Generation and Storage Systems (PGS), Faculty of Electrical Engineering and Information Technology / E.ON Energy Research Center, RWTH Aachen University, Mathieustrasse 10, 52074 Aachen, Germany November 2014 ABSTRACT Wind energy is one of the most important renewable energy sources in Germany and plays a key role regarding energy and climate policy targets of the German government. However, a further diffusion of wind farms involves strong spatial implications that refer to various adverse effects on landscape (onshore wind), noise level, and wildlife. Negative environmental impacts caused by the sometimes suboptimal siting of wind farms have induced an increasing gap between the social acceptance of this technology on the global and local levels. Particularly on the local level, siting processes of wind farm projects often trigger public protest. The aim of this paper is to improve the siting assessment by providing a holistic multi-criteria decision making approach that incorporates techno-economic, socio-political, and environmental criteria, which are defined in a way that social acceptance-related issues are specifically emphasized. We apply a GIS-based Analytic Hierarchy Process approach, where a group of local experts is asked to pairwise compare the incorporated criteria in order to derive the relative importance of each criterion. The results obtained indicate that 9.4% of the study area is still available for wind energy development, whereas only 1.74% of the region is characterized by high suitability. In particular, the northern part of the region still offers substantial unexploited wind energy potential. A comparison with the location of existing wind farms and a sensitivity analysis validate the reliability and accuracy of the model results. Keywords: Wind farm siting, Multi-criteria decision making, Analytic hierarchy process, GIS JEL Classification: C61, Q42, R10 * Corresponding author. Tel.: +49 (0) 241 80 49 831, Fax: +49 (0) 241 80 49 829, E-mail: [email protected] aachen.de (Y. Sunak). 1 1. INTRODUCTION In the light of climate change, rising energy prices, and increasing concerns about the security of energy supply, countries such as Germany foster the diffusion of renewable energy technologies. With ambitious energy and climate policy targets, the German government aims at increasing the share of renewable energies in gross energy consumption to 35% by 2020 and to 80% by 2050 in order to reduce greenhouse gas emissions to 40% and 80-95%, respectively, compared to 1990. The key instrument to achieve this goal is the Act of Granting Priority to Renewable Energy Sources (Erneuerbare-Energien-Gesetz, EEG), which was introduced in 2000 and amended in 2004, 2009, 2012, and 2014. By guaranteeing fixed feed- in tariffs over 20 years, as well as priority purchase and supply of renewable energy, the EEG until 2014 has substantially fostered the market diffusion of renewable energy technologies in Germany. Especially wind energy has experienced enormous growth since 1990. In 2013, the installed capacity of wind energy increased by 3,356 MW to a total of 34,660 MW (BMWi, 2014). The share of wind power in the final energy consumption now accounts for 8.7%, which makes wind energy the largest contributor among all renewables in 2013 (BMWi, 2014).1 The extensive diffusion of wind power in Germany also involves spatial implications. Before the introduction of the EEG, the operation of wind turbines was only profitable in locations with very good wind conditions, mostly in the northern coastal regions. However, with the technological development of wind turbines and the decrease in electricity generation costs, wind energy also became profitable in central and southern parts of the country. Consequently, the number of installed wind turbines has increased from 13,759 to 24,193 within the last decade alone (AEE, 2014). Accompanied by the extensive spatial diffusion of wind farm sites in Germany, one of the most important associated issues is the social acceptance of this technology. Several surveys (e.g. Bell et al., 2005; Devine-Wright and Howes, 2010; Huber and Horbaty, 2012; Kann, 2009; Wolsink, 2007) show that there is a gap between global and local attitudes towards wind energy. While there is a commonly positive attitude towards wind power in general, negative attitudes, such as the not-in-my-backyard syndrome (NIMBYism), are prevalent on the local level, where residents are directly confronted with planned wind farm projects in their neighborhood (Burningham, 2000; Krohn and Damborg, 1999; van der Horst, 2007; Wolsink, 2007). Local negative attitudes towards wind power development most often stem 1 Wind energy accounts for 35%, biomass for 31.4%, solar photovoltaics for 19.7%, and hydro power for 13.9% of the electricity produced by renewables (BMWi, 2014). 2 from the visual and scenic intrusion of the turbines. Besides the general visibility of wind farms in the landscape, shadow flickering effects, which are caused by rotating rotor blades, and noise emitted by wind turbines, often result in annoyance and lead to rejection of wind energy on the local level. Apart from these impacts on humans, wind farms can also have negative effects on flora and fauna, particularly on birds and bats (Manwell et al., 2009). However, the first and typically most important step to improving local attitudes towards wind farms is the conduction of a careful and thorough siting pre-assessment (Ledec et al., 2011). The siting procedure for wind farms in Germany is most commonly based on an exclusion approach, which is derived from legal and factual aspects. Thus, areas are excluded which lack sufficient average wind speeds, as well as areas where wind farm siting is restricted, such as residential areas, natural resources areas (flora-fauna-habitat (FFH) areas2), water bodies, or federal highways and other roads. Furthermore, certain buffer zones are assigned around those areas which are subject to political considerations of the planning authority. Here, the preventive distances from residential areas for avoiding noise nuisance and natural environments to protect avian wildlife are defined. These buffer zones are flexible and their application has to be justified case-by-case by the planning authority (e.g. the municipal administration). After the consideration of all restrictions, and the associated exclusion of those areas, the remaining areas are examined individually. In this step, location-specific considerations will be included to assess whether a site is suitable or not. However, each federal state issues its own policy regarding the siting assessment of wind farms. As a consequence, minimum distances between wind turbines and residential areas, for instance, may vary substantially across the sixteen federal states of Germany. However, this standard exclusion approach for wind farm site pre-assessment does not allow for a precise and differentiated evaluation of site suitability. Basically, only restricted areas are excluded from the development of wind energy. But not all sites are equally suitable for the utilization of wind energy. For example, areas which are far away from residential areas or places of interest are likely to be socially better accepted, since the noise nuisance and the visual impact on residents decrease. Thus, larger distances from urban areas or places of interest increase the suitability from a social acceptance point of view. The suitability of areas might also improve with increasing distance from natural environments, since the adverse effects

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