Development of an Open Source GIS Based Decision Support System for Locating Wind Farms in Wallonia (Southern Belgium)

Abstract

Energy policy is central to any country development. It covers not only economic but also social and environmental facets. Choices that have to be made in the scope of energy policy context require appropriate analytical tools and involve participatory processes (Stagl, 2006). Wind energy appears to be one of the most promising resources with a total installed capacity of 120.8 GW at the end of 2008 (GWEC, 2008). As a signatory of the Kyoto Protocol, Belgium is committed to reducing its GHG emissions by 7.5% between 1990 and 2010. The promotion of renewable energy sources is one of the measures for achieving such an objective, especially through the development of wind farms. Walloon authorities, in Southern Belgium, plan to produce 2,250 GWh with onshore wind turbines on the horizon 2020 (Econotec, 2009). This will represent 7.5 % of the region electricity consumption. However, the development of this so-called clean energy has become an increasing source of conflicts. Most opponents complain about the negative visual impacts on landscapes (Gamboa & Munda, 2007; Rodman & Meentemeyer, 2006). Indeed, turbine blades can reach heights of up to 180 m above ground level and can be seen from distance over 20 km. Moreover, this kind of artificial structures is likely to cause significant noise nuisance, electromagnetic interference, disturbance of local wildlife, and others (Sparkes & Kidner, 1996). The decision-making process regarding the location of wind energy plants is typically multifaceted. Criteria related to economic, technical, environmental and social factors have to be combined in an appropriate manner (Cavallaro & Ciraolo, 2005). As often suggested, a participatory process involving stakeholders with a more or less important say is central to this decision-making scope (Rauschmayer & Wittmer, 2006). According to recent literature review, multi-criteria decision analysis (MCDA) techniques, and more specifically spatial multi-criteria decision analysis or SMCDA (Zucca et al., 2008), are most appropriate to help decision makers in such a context. This study was ordered by Walloon authorities who are involved with the appraisal of numerous wind farm projects initiated by private investors. It is two-fold: