A novel optimal placing of solar farms utilizing multi-criteria decision-making (MCDA) and feature selection

Abstract

Optimal planning of solar farm as a complex multi-criterion decision-making (MCDA) problem is to determine the optimal location to benefit the maximum potential of solar energy. In this research, GIS (geographic information systems)-MCDA methods in determining a suitable area to construct solar farms are applied. To reach this goal, fuzzy-AHP (analytical hierarchy process) and fuzzy-ANP (analytical network process) methods are utilized. Thereafter, the feature selection algorithm extracts important enough parameters to propel solving procedure in such sophisticated problem. The results indicate that combining the fuzzy-ANP method and feature selection algorithm leads to a more accurate method in comparison with AHP and ANP solely. More precisely, by decreasing DPTL and distance to road amounts in east and south of the study area, the fuzzy-AHP method indicates the unsuitable location for solar farm placement, however, decreasing these parameters makes the regions to be a good place for solar farms as the fuzzy-ANP method prove it. Finally, the results indicate that the north of the study area has the highest potential to be the host of solar farms.