This study explores the integration of Autoencoders and clustering techniques within the framework of Geographical Information Systems (GIS) to identify optimal locations for Solar PV (Photovoltaic) installations. By harnessing advanced machine learning methodologies in conjunction with spatial analysis, this research aims to offer a novel approach, distinct from previous studies in this field. Through the analysis of diverse environmental, climatic, and topographical factors, the proposed autoencoder and clustering-based methods provide a holistic solution for identifying areas with peak solar energy potential. The results outline vast swaths of land in different regions in India that can be considered for surveying in preparation for solar PV plant setup. Particularly, results identified large swaths of suitable lands in the states of Rajasthan, Gujarat, and Maharashtra for Solar PV plant setup. These outcomes not only underscore the efficacy and robustness of the suggested approach but also highlight its prospective applications in the broader scope of renewable energy planning.