Exploring the Tradeoff between Installed Capacity andUnserved Energy in Rural Electrification

Abstract

peer reviewedWith the current goal of reaching a 100% electrification rate of the world population, the importance of PV/battery orsolar home systems (SHS) grows as the one of the most viable solution for the most remote and scattered communities.Their modularity and capacity to harvest local resources is particularly relevant for that purpose. The stochasticity of solarenergy and of the demand can however lead to energy shortages in the most critical periods of the day, while an over-sizedsystem represents an important increase in the levelized cost of energy (LCOE). To capture these dynamics and the trade-off between installed capacity and lost load probability (LLP), 16 different demand scenarios are modeled and analyzed.An optimal size for SHS is determined using a linear programming model with different levels of LLP in each scenario. TheDemand time series are constructed using a stochastic demand generator that simulates the behavior of each applianceon a household. The information to create the base-case scenario was obtained with field surveys of a rural community inCochabamba, Bolivia (Raqaypampa). Each scenario has different combinations of appliances, including the intensive useof radio to comply with guidelines of remote education (due to the COVID-19 crisis). The result shows that there is a highreduction of the LCOE in the lower range of LLP. This reduction reaches a breaking point where a higher LLP does notrepresent a significant further reduction of the LCOE. An empirical mathematical formulation is proposed to calculate thisinflection point and a Pareto front plotted to assess the tradeoff between quality of service and LCOE