Introduction: In its recent Energy Plan, Rwanda stated its desire to increase
Independent Power Producers (IPPs) are looking for safe investment environments. For this reason, it is important to be able to model and design the potential electrical consumption of not-yet-electrified communities. Furthermore, it is also beneficial to have a sense of load increase in the near future. This information will justify the business case for private investors and encourage them for implementations.
In light of the above, this project aims at sifting through available literature in terms of scientific publications, technical reports, survey data etc. There are research works focusing on the correlation with certain socio-economic features of a community and its electricity consumption. With this correlation, it is possible to estimate the post-electrification behavior of communities by comparing them with other communities having similar features. This will make rural electrification projects in Rwanda more realistic and reliable.
Method/Case Study: Data resources such as World Bank, African Union, and EU-Africa Energy Partnership will be carefully reviewed. Data which can help will be documented and listed based on country, region, and continent (such as data pertaining to Rwanda, data pertaining to East Africa or Great Lakes region and data pertaining to Africa or Latin America).
Results/Conclusions: This will serve as a stepping stone for future research work focused on Rural Electrification in Developing Countries. Some of the contributions will be:
- Having a guide for renewable energy potential for different countries and regions
- Knowledge of settlement patterns and population densities
- Availability of different resources in different places for microgrid feasibility studiesInformation on socio-economic parameters of certain locations and their load profile
- Information on socio-economic parameters of certain locations and their load profileEstimation of load profile of unelectrified locations based on other locations with similar parameters
- Estimation of load profile of unelectrified locations based on other locations with similar parameters