The OnSSET Model ================ This section presents the overall methodology of the OnSSET tool, based on an excerpt of the PhD thesis `New methods and applications to explore the dynamics of least-cost technologies in geospatial electrification modelling `_ by A. Sahlberg (2023): The electrification problem consists of solving four distinct problems to identify which technology can supply the electricity demand in each location at the lowest cost `Ciller and Lumbreras (2020) `_: 1) assigning households and other demand nodes into relevant clusters to evaluate the least-cost technology for, 2) calculate the distribution network required within each cluster (depending on technology), 3) identify the network for new grid-extension and 4) selecting the least-cost technology in each cluster. The following steps are undertaken to perform all of these tasks using the OnSSET tool: The first step is to create the settlements that form the basis of the analysis. High-resolution population data is clustered into vector polygons. In the second step of the analysis, geospatial information is collected and extracted to each of the settlements in the analysis. This includes e.g. information about the energy resource availability, distance to roads and existing power infrastructure (e.g. MV lines, LV lines, substations, distribution transformers and mini-grids), land cover, elevation and night-time lights, locations of other electricity demands such as schools and health facilities. Note that the geospatial information required varies depending on the scope of the study. .. figure:: img/methodology_gis_information.png :align: center Geospatial information used in geospatial electrification modelling to understand settlement characteristics Once the geospatial data has been processed, the settlements that are already electrified are identified. As this information is usually not available as a geospatial dataset, night-time lights, population data and existing infrastructure GIS data are used to calibrate the model against the national statistical electrification rate. Settlements with night-time lights that are close to the existing power infrastructure are considered likely to be electrified. Furthermore, a settlement can be considered 35 partially electrified if there is only night-time lights in some areas of the settlement (identified by overlaying the raster night-time light data with the raster population data during the creation of population settlements in step 1). In the fourth step, the model is calibrated and can be used to run scenarios. The first step of a scenario is to project the population growth for the years of analysis (based on urban and rural population growth rates), and to estimate the electricity demand in each settlement. The demand estimate can be performed using different target levels e.g. for urban and rural settlements, by classification based on socio-economic information such as GDP and poverty rates, or any other method. Often, demand estimations are used in the context of the Multi-Tier Framework (MTF) (`Bhatia and Angelou, 2015 `_), which define five Tiers of electricity access that enable various electricity services. Additionally, the model is equipped to be able to include demand from other sectors as well, assuming such information is available. Once the demand has been estimated in each settlement, the least-cost off-grid technology is identified. The selection of technologies is based on the technology that can meet the demand at the lowest Levelized Cost of Electricity (LCOE). The LCOE takes into account all of the costs (investment, fuel, operation and maintenance) over the project life-time divided by the electricity demand supplied to calculate the cost of electricity (USD/kWh) for the project to break even. The LCOE concept is useful to compare technologies with different cost structures (`Nerini et al., 2016 `_). When the least-cost off-grid technology has been identified in each settlement, a grid-extension algorithm identifies where extension of the centralized grid network can supply electricity at a lower cost than the least-cost off-grid alternative (taking into account both the cost of extending the grid lines there, the distribution network required within the settlement, and the generation cost of electricity for the centralized grid). Following this step, the least-cost technology has been identified in all settlements. .. figure:: img/methodology_results.png :align: center Final least-cost technology selection The OnSSET tool is equipped with a time-step functionality. If the target electrification rate is less than 100%, the settlements that should be electrified first are identified based on the user-specified prioritization (e.g. the settlements with the lowest LCOE, or the most accessible settlements). This then serves as a starting point for the next time-step, which starts again from step 4.