PV POWER PLANTS SITES SELECTION USING GIS-FAHP BASED APPROACH IN NORTH-WESTERN MOROCCO
Keywords: Fuzzy Analytic Hierarchy Process, Geographic information system, Multi-Criterion Decision Analysis, Solar photovoltaic power plants, Renewable energy, Photovoltaic potential, Installation capacity, Northwestern Morocco
Abstract. Energy plays a crucial role in the economy of any country. One of the most recent trends in global development is the transition to "green” growth. Morocco is keeping pace with its growth by promising to increase renewable energy capacity to 42% of total installed capacity by 2020 and to 52% by 2030. This study develops a framework that aims to determine the optimal areas for deploying photovoltaic (PV) installation in two stages. The first stage aims at excluding the undesirable areas such as forests, rivers and agricultural land. The second stage consists in defining the suitability of sites based on seven criteria; solar irradiation, land surface temperature, slopes, slope orientation, distance from power lines, distance from main roads, distance of urban area. In this study we are using fuzzy logic and fuzzy membership functions in order to create criteria layers in the environment of Geographic Information System (GIS) that allowing the integration of a Multi-Criterion Decision Analysis (MCDA) to identify the best sites to deploy PV solar power plants in north-western Morocco. Also, the Analytic Hierarchy Process (AHP) technique is used to determine weights for each one of the criteria. Results obtained from the spatial approach shows that the major portion of the studied area was judged inappropriate for solar farms installations. Also, it shows that only 5.11% (8500 Ha) of the territory demonstrate high suitability for PV solar installations located in the southern part of our studied area with a potential of electricity generation, from the areas with high suitability level, assuming a PV system efficiency of 6.48%; equivalent to 5.39 Twh/year with an installed capacity of 4.02 GW and an annual carbon emission reduction of 3 697.54 Kt-CO2/year. The resulting suitability map can be used as a decision support tool to help the public policy makers to integrate green energy into their policies.