Clustering Techniques for Secondary Substations Siting

The scientific community is active in developing new models and methods to help reach the ambitious target set by UN SDGs7: universal access electricity 2030. Efficient planning of distribution networks a complex multivariate task, which usually split into multiple subproblems reduce number variables. present work addresses problem optimal secondary substation siting, means different clustering techniques. In contrast with majority approaches found literature, are devoted MV grids already electrified urban areas, this focuses on greenfield rural areas. K-means algorithm, hierarchical agglomerative clustering, method based weighted tree partitioning adapted run two real case studies, population densities. algorithms compared terms indicators useful assess feasibility solutions found. have proven be effective addressing some crucial aspects substations siting constitute relevant improvements classic approach literature. However, it that very challenging conjugate an acceptable geographical span area served single power high enough justify installation when load density low. other words, well known standards adopted industrialized countries do not fit countries’ requirements.