Artificial intelligence for transmission expansion planning in Sub-Saharan Africa

Abstract

Transmission networks are facing very demanding challenges in Sub-Saharan Africa: African utilities are focused on rural electrification, as the access to power is limited to 32 % of the overall population; load increase rates are very high; the connection of renewables and new bulk generation requires interconnection to already existing transmission grids, in some situations thousands of kilometers long; interconnectivity among Southern Africa Power Pool (SAPP) systems is very weak; the existing infra-structure requires improvement and maintenance. As a result of all these concerns, SAPP has already identified transmission expansion as one of the most important issues to be addressed on the next years in Southern Africa. It is also important to recognize that the connection of new generation plays an important role on interconnectivity amongst Sub-Saharan African countries, as relevant energy sources are typically located very far from the main consumers, and are often located in different countries. This is a quite different paradigm from that what is normally found in other continents. Huge investment is needed to implement new transmission projects; and investors have to be identified outside the region. These investors require well established technical and stable legal frameworks. Both local stakeholders and investors need suitable dynamic tools to model the expansion of the systems. On these tools one has to take into account the complexity of the system on both space and time dimensions. Artificial intelligence based models, like Evolutionary Particle Swarm Optimization (EPSO) either real or discrete approach, have already been tested in real transmission networks, and may be also useful to plan the future Sub-Saharan transmission network. In this scope, this paper aims at describing a mathematical model to perform long term transmission expansion studies having a multiyear nature in order to identify the most adequate expansion plan while considering a number of criteria as the investment and operation costs, the reliability of operation and the uncertainties on loads.