Cameroon is a country located in west-central Africa with an area of approximately 475,000 km2 for 26 million inhabitants. With a national electrification rate of 63%, only 20% of the population would actually have continuous access to electricity. Access remains the big challenge. This presentation shows how the combination of geospatial data and the GEP-OnSSET tool as well as demographic and poverty indices are used to produce electrification access scenarios. The results highlight the geographic distribution of the types of energy that can be used to increase access to electricity at the lowest cost in Cameroon by 2030. The Far North region of the country has a potential for GHI irradiation to produce autonomous PV electricity. However, Cameroon does not recognize off-grid technologies such as Solar Home System and PV mini-grid as leverage to increase the electrification rate. Off-grid technologies represent an opportunity to increase the national electrification rate with the participation of NGOs, mini-grid and off-grid developers, civil society and Governments. Future work will explore additional scenarios taking into account the country's electrification policies with advocacy with the authorities. In addition, capacity building sessions with the private sector and governments are to be carried out to transmit knowledge of the GEP-OnSSET tool.

Cette présentation constitue le résultat d'une activité de renforcement des capacités de trois semaines sur GEP-OnSSET dans le cadre de l'atelier 2023 de la Plateforme de modélisation énergétique pour l'Afrique (EMP-A). OnSSET est un outil SIG open source développé pour identifier la ou les options d'électrification les moins coûteuses parmi sept configurations alternatives.

This presentation constitutes the outcome of a three-weeks capacity building activity on GEP-OnSSET as part of the 2023 Energy Modelling Platform for Africa (EMP-A) workshop. OnSSET is an open-source GIS based tool developed to identify the least-cost electrification option(s) between seven alternative configurations.