Abstract
As global wind energy capacity continues to expand, the need to site commercial wind farms in productive, affordable, and technically feasible locations has become increasingly important. The use of wind farm site suitability models to identify these locations has grown consequently, thus increasing interest in standardizing certain aspects of these models' development. This systematic review of wind farm site suitability studies seeks to identify similarities and differences in the selection and representation of their enlisted siting factors. The review focuses on how subjective modeling decisions, such as vocabulary choices and dataset selection, occur in the literature, based on five identified themes: 1) Deciding Upon Siting Factors, which explains how a study's geographical context, selected modeling approach, and modeler decisions can influence siting factor selection; 2) Classifying Data and Siting Factor Terminology, which addresses the extent and the advantages of consistent siting factor vocabulary; 3) Implementing Siting Factors as Constraints or as Evaluation Criteria, which covers the importance of consistent implementation and of specifying logic when enlisting siting factors to assess potential wind farm sites; 4) Utilizing Primary and Secondary Data, which details how a study's reliance on external or self-collected datasets influences siting factor representation; and 5) Data Source and Accessibility, which highlights the inconsistent provision of citations and dataset sources, and the availability of datasets for siting factors to the broader scientific community. Standardizing the selection and representation of siting factors would benefit comparisons between wind farm site suitability studies and communication of model outputs to a wider audience.