Abstract
Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare our method with a quick estimation similar to the ones most regional planning tools apply, showing the effectiveness of our method.
Highlights
The current methods that estimate the network costs of mini-grids in the literature are oversimplified, require a significant amount of computation time, or it is unclear if they could be applied in large-scale planning
The length of the minimum spanning tree (MST) linking all consumers is calculated with the consumers of the mini-grid and the generation site located at the demand-weighted center of the minigrid, which is an appropriate placement for the generation site
The aggregated demand is scaled by an estimation of the network cost per kWh in the analysis region, which could be obtained by expert advice or looking at previous reports or publications that deal with electrification planning projects in the corresponding region
Summary
Some models take advantage of Geographical Information Systems (GIS), providing instant access to geospatial data They generally divide the consumers into cells and estimate the levelized cost of electricity (LCOE) of several alternatives to determine the recommended electrification solution of each cell. The current methods that estimate the network costs of mini-grids in the literature are oversimplified (which is the case of most regional planning tools), require a significant amount of computation time (which is the case of REM), or it is unclear if they could be applied in large-scale planning (which is the case of ViPOR and the remaining village-based tools for network designs). The method goes beyond the rules of thumb that most regional planning models apply It avoids the computational burden of explicitly calculating the detailed layout of the network considering electric constraints and power flows (such as REM does). It considers spatial metrics relatively fast to calculate, such as the length of the minimum spanning tree (MST) that links all the consumers and
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