Kruskal's Algorithm, Vogel's Approximation and Modified Distribution Methods for the Design of Optimal Electrical Networks in the Democratic Republic of Congo

摘要

People who are familiar with the Democratic Republic of Congo (DRC) know its richness in terms of precious minerals; they even call DRC a “geological scandal”. One should know that DRC is also a scandal in terms of energy resources for electrification. The DRC has a hydroelectric potential estimated to one hundred Gigawatts (100 GW), with large reserves of oil, natural gas and coal. DRC has a considerable daily potential of photovoltaic energy, estimated between 4 and 6 kilowatt-hours per meter-square per day (kWh/m²/day) of Global Horizontal Irradiation (GHI). It has a significant biomass energy potential around 300 to 700 Gigawatt-hour per year from agricultural waste. The country has uranium mining and can therefore invest in electricity production using uranium-based nuclear fission. However, according to the World Bank, less than 19% of the Congolese have access to electricity to-date. It is therefore imperative to develop safe and reliable strategies to convert these potential electricity sources into usable resources, and above all to ensure that all Congolese households have access to electricity. This paper discusses Kruskal's algorithm, Vogel's approximation method and modified distribution method as efficient optimization tools for electrical networks design in general, and particularly in the context of electricity distribution in the DRC.