Application of Ahp and Gis for Optimal Solar Site Identification in Madhesh Province, Nepal

Abstract

Solar-based renewable energy adoption is in its early stage in the power system of Nepal complying with its commitment to carbon neutrality. The government of Nepal has declared a goal of setting up solar power plants of at least 200 MW in Madhesh Province, but the selection of optimal sites will be the decisive factor in achieving this goal. Therefore, rigorous investigation is necessary for optimal site selection. A three-step framework combining the Analytic Hierarchy Process (AHP) and the Geographical Information System (GIS) has been adopted to identify the optimal location for solar power plant installation in Madhesh Province. The framework includes the creation of weighted individual raster images for the different criteria, images of restricted areas for solar installation, and a combination of all the rasters into a single raster using GIS-based software. The weights of the criteria and sub-criteria have been evaluated using the AHP model, which is an expert judgments-based model. The criteria considered were solar irradiance, annual mean temperature, distance from the road, distance from the substation, distance from the urban area, elevation, aspect, and land use. The results were graded from the least preferred area to the most highly suitable area. The most highly suitable areas were in the Saptari, Siraha, Dhanusa, and Mahottari districts, while the districts in the western region of the province had less suitable areas. Thus, the province’s eastern region is most suitable for installing solar power plants.

Decision Support System for Bioenergy Supply Chain Optimization: A Case Study at Lebak District, Banten Indonesia

“…Differences influence insignificant differences in results in analysis periods, concepts and limitations on agricultural sites, data sources and scales, mapping methods, and area coverage. Previous research determined bioenergy agroindustry location by multicriteria analysis integrated with the GIS model for selecting the best bioenergy agroindustry site candidate [26,27].…”

Implementation of Gis-Ahp-Owa for Land Suitability Assessment in Infrastructure Investment Projects: A Case Study in Yucatán, Mexico

“…In contrast, other LSA approaches have used GIS remote sensing (Vasu et al, 2018;AbdelRahman et al, 2016;Halder, 2013;Bandyopadhyay & Jayaraman, 2009;Quan et al, 2007), parametric methods (El Baroudy, 2016Rabia & Terribile, 2013), decision trees (Bydekerke et al, 1998), logic networks (Stoms et al, 2002), fuzzy sets (Karasan, 2019;Zhang et al, 2015), and compromise programming (Thinh et al, 2004). In the International Journal of the Analytical Hierarchy Process, the location of optimal infrastructure investment sites has been developed using GIS-AHP (Shrestha et al, 2022;Otay & Kahraman, 2018;Minhas, 2015;Lami et al, 2011;Girard et al, 2012). However, none of these approaches involved the OWA operator.…”