An interaction model applied to optimize photovoltaic farm location: A case study of China

Given the escalating environmental challenges and the looming carbon peaking and carbon neutrality goals, developing renewable energies becomes a global imperative. The pivotal initial stage involves site selection; however, this process has been plagued by the ambiguity of subjective decision-making and the inconsistency of multi-factor decisions. In this regard, this study proposes a new evaluation system which combines Geodetector and Interaction Linear Model to minimize subjective interventions and reveal the mechanisms by which interaction terms influence siting. China is selected to unveil the model's capability through solar PV site selection. The results indicate that compared with the Basic Linear Model, the Interaction Linear Model increased the estimation accuracy by 8%, with some interactive terms showing higher determinant power than single factors. Based on this interaction model, there is a total of 13% of China's land is developable for solar PV plants, consisting of 46% highly suitable areas (581,576 km2), 39% moderately suitable areas (492,615 km2), and 15% marginally suitable areas (198,088 km2). Finally, Xinjiang was identified as the most suitable place in China. Above all, the new siting system proposed here provides a new perspective on renewables' site selection, promoting the high-quality energy transition globally.