Holistic geospatial data-based procedure for electric network design and least-cost energy strategy

The identification of the best electrification strategy is a fundamental step to increase energy access in rural areas of developing countries. The objective of the present work is to propose a new geospatial-based procedure for rural electrification planning, able to select and design an effective energy system for a defined geographical region. The least-cost solution among stand-alone mini-grids and connection to the existing national grid of non electrified communities is identified. Spatial information is exploited to compute renewable resources potential, to identify populated areas, subdivide them into clusters, and to design the electrical network connecting the clusters' consumers pursuing the minimization of costs. To this end, an iterative minimum-path algorithm has been developed by the authors. It is able to approximate the Minimum Steiner Tree also for graphs with many terminal points, accounting for a weighted cost surface, which represents the real cost of installing electric feeders in difficult areas. The performance of the procedure has been tested in the rural area of Namanjavira, in the Zambezia Province, Mozambique, where 6 microgrids and 2 interconnected grids were designed. The inclusion of distribution grid costs and penalties related to real terrain morphology lead to a significant increase (up to 200%) of the total cost, highlighting the cornerstone role of a spatial approach in the identification of the best electrification strategy.