## 2 Methodological Framework  
Most scientific research carried out on the theme of selecting locations for wind farms is based on the combined application of GIS and other methods of multi-criteria analysis. [PERSON] et al. [4] affirmed the use of GIS when selecting locations for wind farms by developing a tool to determine the most favorable location for wind farms in New York State, based on SMCA (Spatial MultiCriteria Analysis). [PERSON] et al. [15] highlighted the complexity of decision-making with regard to the location of wind farms and proposed the use of the PROMETHEE II MADM METHOD to conduct a GIS analysis on the suitability of various locations. [PERSON] et al. [5] used GIS and MCDMA methods (AHP, OWA, OCRA, VIKOR and TOPSIS) to determine the most favorable location for wind farms in mainland Ecuador. Some scientists also rely on the independent application of multi-criteria methods. [PERSON] et al. [16] proposed the use of the innovative PROMETHEE method integrated with conflict analysis to solve MCDMA problems consisting of quantitative and qualitative criteria. [PERSON] et al. [17] used the PROMETHEE method of multi-criteria analysis to determine the most suitable wind farm locations in Saudi Arabia. In contrast to the research mentioned above, this paper does not take the criterion of wind speed into account since it is considered to be the starting point, i.e., the main prerequisite for locating wind farms. Determining the wind potential and estimating the production precede the selection of the micro-location of a wind farm, based on empirical data from previously conducted macro-level measurement campaigns carried out by state institutions or investors. It is logical that areas with average wind speed values below the cost-effectiveness limit are omitted from any further evaluation. One characteristic of this paper is its simplification of the methodological procedures used in the evaluation (MCDMA, GIS, PROMETHEE), which increases the likelihood of its use by interested experts. A particularly significant part of the research is the fieldwork carried out by the authors since they visited each of the candidate locations in order to determine the factual situation for assessing the individual evaluation criteria. As seen in Figure 1, the first stage in selecting a wind farm location is the elimination stage, in which unfavorable locations are identified based on elimination criteria. The first step is to identify those criteria. Figure 1: Procedure for selecting the location of wind farms based on the principles of the GIS and PROMETHEE methods. Elimination criteria are based exclusively on spatial data and rooted in the relevant legislation and empirical standards in the field of wind energy (required distances from protected areas, inhabited places, buildings, infrastructure corridors, etc.). They are the product of local legal regulations and the results of software modeling, based on a large number of empirical samples. This paper uses the authors' empirical data on the significance of individual criteria for selecting locations, obtained during the development of the following wind power projects in the Republic of Serbia: Maestrale Ring (800 MW); Vetrozelena (300 MW); Lovenca (300 MW); Cibuk 1 (158 MW); Crni Vrh (150 MW); Bela Anta (120 MW); Kosava (105 MW); Feketic (90 MW); and Nikine Vode (45 MW). These make up a representative sample. Bearing in mind the importance, but also the specificity of legislation in the field of wind power, both locally and globally, the elimination criteria may only slightly differ from country to country and from continent to continent. Apart from these small differences in quantitative statements (necessary distances), they can be considered universal. Table 1 presents the elimination criteria for an area of the Republic of Serbia, which is situated in Europe. The authors had access to all the relevant regulations and spatial data for these criteria necessary for implementing the elimination phase.