Solar power plant site selection modeling for sensitive ecosystems

Reducing dependence on fossil fuels and increasing energy production based on renewable energy sources is a powerful alternative to alleviate global ecological problems. However, renewable energy facilities that require the use of large areas can lead to deterioration of ecological integrity, decrease in agricultural capacity, interruption of the continuity of habitats, and destabilization of the microclimate. Therefore, the site selection for renewable energy facilities is a challenging issue that needs to satisfy economic efficiency by not overlooking ecological sensitivity. In this study, two different site selection models have been developed for solar power plants to determine the ideal locations where economic efficiency is the highest and ecological sensitivity is the lowest. A geographic information system-based multicriteria decision-making method was applied with combining analytical hierarchy process. Economic suitability is determined using 17 criteria, and ecological suitability is determined using 13 criteria. For economic suitability analysis, global horizontal irradiation, solar radiation, sunshine duration, aspect, topographic shadow, and average land cost criteria were determined as the essential criteria. For ecological suitability analysis, distance to conservation areas, ecosystem services, land cover, natural integration potential, vegetation index, and land use capability were the most dominant criteria. Almost 76% of the study area needs to be ecologically protected and therefore was restricted. The results of economic suitability analysis show that approximately 13% of the total area is secondary suitable, 82% is tertiary suitable, while the primary suitable area is negligible. As a result of the ecological suitability analysis, the fourth- and fifth-grade suitable areas constitute approximately 98% of the total area. Consequently, ideal locations for solar power plants that provide economic efficiency and ecological sensitivity have been identified for Kirklareli. The proposed methodology can contribute to site selection literature in the development of an ecological sensitivity perspective. Moreover, it can be used as a decision support tool by local governments and renewable energy entrepreneurs for selecting the most suitable areas.