The increasing demand for electricity and the efforts to reduce the environmental impact of fossil fuel-based power plants have made new and renewable energy sources,
particularly solar power plants (PLTS), a potential strategic solution for substations. This can be achieved through spatial analysis and data clustering methods. This study aims to determine the potential penetration of solar power plants in the Jakarta substation area using K-means clustering and digital mapping based on geographic information systems (GIS). The study used 62 substation locations and six electrical and environmental variables: transformer voltage, number of transformers, total transformer capacity, average temperature, solar irradiance, and solar panel output productivity (PVOut). The data processing began by determining the number of clusters. Then, each cluster count was evaluated using three methods the Elbow method, Silhouette Efficiency, and the Davies-Bouldin Indeks to identify the optimal number of clusters. Ultimately, five clusters were selected as the best option. Clustering results revealed significant differences in characteristics between clusters in terms of electrical and environmental factors. Digital mapping was then performed in a geographic information system to clarify the spatial distribution of cluster patterns. Using the HelioScope platform, the PLTS simulation design estimated the annual electricity production of each cluster to be between 162.8 and 164.9 MWh, with a total annual energy production potential of 10.16 GWh from all substations. These results confirm that solar power plant penetration at Jakarta substations could support savings in conventional power plant electricity consumption and help achieve the national renewable energy mix target.