Solar Farm Suitability Using Geographic Information System Fuzzy Sets and Analytic Hierarchy Processes: Case Study of Ulleung Island, Korea

Solar farm suitability in remote areas will involve a multi-criteria evaluation (MCE) process, particularly well suited for the geographic information system (GIS) environment. Photovoltaic (PV) solar farm criteria were evaluated for an island-based case region having complex topographic and regulatory criteria, along with high demand for low-carbon local electricity production: Ulleung Island, Korea. Constraint variables that identified areas forbidden to PV farm development were consolidated into a single binary constraint layer (e.g., environmental regulation, ecological protection, future land use). Six factor variables were selected as influential on-site suitability within the geospatial database to seek out increased annual average power performance and reduced potential investment costs, forming new criteria layers for site suitability: solar irradiation, sunshine hours, average temperature in summer, proximity to transmission line, proximity to roads, and slope. Each factor variable was normalized via a fuzzy membership function (FMF) and parameter setting based on the local characteristics and criteria for a fixed axis PV system. Representative weighting of the relative importance for each factor variable was assigned via pairwise comparison completed by experts. A suitability index (SI) with six factor variables was derived using a weighted fuzzy summation method. Sensitivity analysis was conducted to assess four different SI based on the development scenarios (i.e., the combination of factors being considered). From the resulting map, three highly suitable regions were suggested and validated by comparison with satellite images to confirm the candidate sites for solar farm development. The GIS-MCE method proposed can also be applicable widely to other PV solar farm site selection projects with appropriate adaption for local variables.