Locating of Wind Power Farms by Analytic Hierarchy Process Method (Case Study: Sistan and Baluchistan Province, Iran)

Abstract

Limitation of fossil energy reserves in the world and increasing level of energy consumption, have always challenged human to replace new energy sources. Meanwhile, wind power as one of the new aspects of energy is of a special place. Due to the topography of the Sistan and Baluchistan province and its relative position, it is one of the best places to build wind farms. The aim of this study was to determine suitable locations for the construction of wind farms in the province. The following criteria were considered for various standards and due to the importance of data integration, Analytic Hierarchy Process (AHP) method was selected and implemented to weight the layer through Expert choice software. ArcGIS was used for layers spatial analysis and overlapping. After data analysis, the studied region, in terms of the susceptibility to build wind farms, was divided into four levels: excellent, good, fair, weak. Results indicated that GIS as a supportive and decision making system is helpful preparing data and modeling priorities and experts comments regarding various factors and help designers selecting a suitable place to build wind farms. In this study, we determined three priorities for the construction of wind farms, taking into account the limited overlap and conformity of limitations map and locating, the area of prioritized region, climate and the field observations; the priority order is excellent, good, average, including Zabol, central regions in Zabol and Chabahar.

Location Selection forWind Turbines in Balıkesir, NW Turkey, Using GIS

“…Location selection for wind power plants (WPP) is a complex issue which involves various factors such as physical, economic, environmental effects, visually and planning (Baban & Parry, 2000). In order to determine a comprehensive set of criteria, the "Regional Wind Resource Information Report" published by the Directorate of Renewable Energy and relevant previous studies (Bennui et al, 2007 Baban & Parry, 2000, Özşahin & Kaymaz 2013, Menduhoğlu et al, 2014, Azizi et al, 2014, Moiloa, 2009, Asadi & Karami, 2017, Crill et al, 2010, Gazioğlu et al, 1997, Haaren and Fthenakis, 2011, Haralambopoulos and Polatidis, 2003Farajzadeh , et al, 2013;Nobre, A., et al 2009, Memduhoğlu, et al, 2014. were reviewed, factors influential for WPP (power density, altitude, exposure, land usage, slope, electricity lines, residential centers, roads, wetlands, coasts, streams, fault lines) were determined, they were subjected to analysis, and spatially the best WPP locations for the province of Balıkesir were found.…”

“…Among the twelve determined criteria, the factor with the highest weight was power density. This is because the most important criterion for measuring the wind energy potential in a geographical region is calculation of power density (Azizi et al, 2014, Asedi andKarami, 2017). This is why its weight value was held higher than all the others (Fig 4a).…”

“…After this analysis, the raster maps created for all factors were assigned with values based on their effect values determined based on the literature reviews and field conditions. Open Areas 0 -1 1 -8 8 -16 16 -32 32 -89 0 -100 100 -500 500 -> 1000 -5000 0 -2500 2500 -3500 3500 -4500 4500 -5500 5500 -> 0 -500 500 -1000 1000 -1500 1500 -2000 2000 -> 0 -2500 2500 -3000 3000 -3500 3500 -4000 4000 -> 0 -2500 2500 -3000 3000 -3500 3500 -4000 4000 -> Baban & Parry, 2000, Özşahin & Kaymaz 2013, Menduhoğlu et al, 2014, Azizi et al, 2014, Moiloa, 2009, Asadi & Karami, 2017, Crill et al, 2010, Gazioğlu et al, 1997, Haaren and Fthenakis, 2011, Haralambopoulos and Polatidis, 2003Farajzadeh , et al, 2013;Nobre, A., et al 2009, Memduhoğlu, et al, 2014. were reviewed, factors influential for WPP (power density, altitude, exposure, land usage, slope, electricity lines, residential centers, roads, wetlands, coasts, streams, fault lines) were determined, they were subjected to analysis, and spatially the best WPP locations for the province of Balıkesir were found.…”

Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model

“…The best and the worst attribute values for each sub-criterion are then calculated and the FPIS and FNIS are obtained. The distances of each alternative from the FPIS and FNIS are measured using Equation (20). After computing the distances from the best and the worst attribute values, the closeness coefficients of the three alternative locations are determined and then the superior alternative is chosen.…”

“…Wu et al [19] proposed a fuzzy ELECTRE-III model to determine potential sites for offshore wind energy development in China. Asadi and Karami [20] used the AHP technique to find the most suitable locations for the construction of a wind farm in Sistan and Baluchistan province in the southeast of Iran. The alternative locations were evaluated based on five criteria, namely climate, geography, socio-economy, environment, and geology.…”