The Congo Epela project

General description

The Democratic Republic of Congo (DRC) has vast energy resources. However, only 9-15% of the more than its 80 million inhabitants have intermittent access to electricity. With this platform, we want to provide data and knowledge to civil society organisations and other stakeholders to contribute to their quest for increased, more equitable, cleaner electricity production and distribution, and to inform future developments and policies in the DRC electricity sector.

This platform is an interactive tool that displays the cheapest solutions to electrify each populated area of the DRC and other useful data for electrification analysis such as electricity demand, energy sources, electric networks, etc. The tool is deliberately focused on the provision of electricity to households through a combination of centralised (grid) and decentralised (mini-grids and solar panels) electrification solutions, rather than only centralised solutions.

The tool is the result of the joint work of Resource Matters, KTH Royal Institute of Technology, the University of Cape Town, the Reiner Lemoine Institute, and several Congolese civil society organisations members of the Mwangaza Network, a coalition of Congolese NGOs aiming to contribute to the recovery of the electricity sector in DRC.

The members of this coalition are the NGOs Initiative pour la bonne gouvernance et droits humains (IBGDH, Lualaba),Observatoire d'Etudes et d'Appui à la Responsabilité Sociale et Environnementale (OEARSE, Haut-Katanga), Justice Pour Tous (JPT, Sud-Kivu), the Cadre de Concertation de la société civile de l'Ituri sur les Ressources Naturelles (CdC/RN, Ituri), the Coalition of Civil Society Organisations for the Monitoring of Reforms and Public Action (CORAP, Kinshasa), the Congolese Centre for Sustainable Development (CODED, Kinshasa), and Afrewatch (Upper Katanga and North Kivu).

Using the tool

The tool has three main pages :

  1. Data: here you can access information on electricity demand, energy resources and existing infrastructure. What is the estimated current electricity demand in the country? What resources are available to meet the needs? Here you can answer these types of questions.
  2. Solutions: on this page you can find out the cheapest and cleanest solutions to electrify the country under different conditions. Should the electricity grid be extended? Should hydro or solar minigrids be built? Or solar panels added on people's roofs? How much would it cost? Questions like these can be answered with the information provided here.
  3. About: here you will find more details about the platform.

On the left-hand side bar, you will find links to the sections of the site, an access to the video explaining how the platform works (camera icon), and the language control (FR or EN).

The easiest way to quickly learn how to use the platform is to click on the video icon at the bottom left of the navigation bar. The tool works best in the latest version of Chrome, Firefox or Edge browsers. There are no cookies or tracking technologies included.

Data section

The section contains the commands shown below.

  1. The “Choose an area menu”, which will zoom in on that province and restrict certain items to show only information about that province, such as the control below. Choose 'DRC' to return to the whole country.
  2. The “Key energy info” button to see key electrification figures for the selected area.
  3. The data categories to display on the map, each containing several data items, which can be turned on or off. When enabled, these will appear on the map, with an entry in the legend to the right. Click on each data category to see all available data layers, including population demand for electricity, existing and potential hydro sites and the electricity grid. Some categories may have filters, which allow you to limit the items displayed according to certain properties, for example, only displaying areas populated by a pre-selected number of inhabitants. By clicking on each of the categories, you will find icons that contain explanations for each data item.
  4. On the map that appears, you can click on a populated area to see useful information about its current status in the electrification and electricity demand variables. Once the window appears, you can click on "Find electrification solutions for this area" to go directly to the map on the "Solutions" page, zoomed in at the same point.
  5. The map is accompanied by a legend that provides information necessary for the understanding of the activated data.

Solutions section

This view has the following controls:

  1. The “Choose an area” menu (same operation as in the data section).
  2. The "Key Energy Information" icon displays the electrification statistics of the selected area.
  3. In the section "Choose the year of the results", you can choose between the "Current year" which shows the current state of electrification in the country, and the other years in the drop-down list which allows to visualise future electrification solutions.
  4. The section "Choose electrification conditions" allows you to select the electrification parameters defining the future scenario you wish to analyse. When you click on each parameter, you will get different levels to select the future electrification scenario. For example, in the solar panel cost parameter, you can choose between high and low cost.
  5. By clicking on "View results" you will be able to see the selected solutions on the map. By changing the year, the map is automatically updated. However, if other parameters are changed, it is necessary to click again on "View results" to update the results. 6.On the map you can see the results based on the parameters you have selected. There you can click on a populated area to see useful information on the cheapest way to bring electrification to that area, including the technology to be used, the energy capacity needed, the number of households to be connected to meet the selected parameters, and the costs involved. 7.The map is also accompanied by a legend that provides information necessary for the understanding of the visualised solutions.

Generating results

The models used to generate the results

As mentioned earlier, the main objective of this tool is to allow stakeholders to visualise solutions for electrifying the country through a series of scenarios. The platform proposes three types of solutions: providing electricity by extending the grid, building mini-grids (solar or hydro) and installing stand-alone systems. The solutions displayed on the platform are the result of the interaction between three components:

  1. A modelling tool called OnSSET that performs the calculations to determine the cheapest ways to electrify the country under different conditions. It is a spatial tool because it provides results for each populated area of the DRC, rather than the country as a whole or each province. It is the backbone of the platform. It was managed by KTH.
  2. A modelling tool called OSeMOSYS that determines the cheapest ways to supply the country's electricity networks under different conditions. It was managed by UCT.
  3. A demand model to estimate the electricity needs of households, productive uses and other actors. It was managed by RLI.

Interaction between the model components

The three components interact as follows::

  1. OnSSET compares the cost of electrifying a community by extending one of three national grids, building a mini-grid (hydroelectric or solar) or installing solar home panels. These costs depend on several factors: the remoteness or not of hydroelectric, solar and wind power sites - potential and existing -, proximity to roads, and technical parameters such as the cost per km of high and medium voltage lines, costs associated with solar panels, etc.
  2. From this comparison, it selects the cheapest way. This selection is relative to the electricity demand in the community. For example, extending the network to a small community may not make sense, even if the said community is close to the existing network, because the demand there might be too low to cover the extension costs. In this case, OnSSET would opt for a decentralized solution. This makes demand estimation a crucial step in solution estimation.
  3. On the other hand, OSeMOSYS determines the least expensive mix of energy sources to supply the country's electrical networks. For example, if it is to be powered by hydro, wind, solar or a mixture of all of these. This mix is ​​fueling demand in communities where OnSSET has determined that the most effective solution is to expand the network, so OSeMosys results depend on OnSSET results. Here is the data used to make these calculations.

The data used to make these calculations are as follows.

Our sources

The full list of our data and sources is below (except for our confidential data). You will also find links to the raw data.

Population demand and electricity accessPlusieurs sources
Other demand sources
MiningResource Matters
Potential and existing energy sites
Hydropower sitesPlusieurs sources
Solar sites Banque mondiale
Wind sitesInitiative d'impact de la recherche de Berkeley
Raw energy resources
RiversRéférentiel Géographique Commun
Solar irradiationGlobal Solar Atlas
Solar potential (PVOT)Global Solar Atlas
Wind speedGlobal Wind Atlas
Electricity network
Existing high voltage lines (no direct current lines)Open Street Map
Existing high voltage lines (direct current lines)Open Street Map
Existing medium voltage linesOpen Street Map
Electric substationsSNEL
More information
Night lightNASA

Other data not displayed in the platform but used in the model:

Province boundariesRéférentiel Géographique Commun
Travel timeMalaria Atlas Project
RoadsOpen Street Map
Land coverUniversity of Maryland

Solutions data

All the CSV files used to generate the solutions for all the scenarios can be found here, as well as the summaries by province for each scenario generated. You can also find documents describing the variables and other technical aspects of the data.

Contributing and development

The platform is mainly developed in the following three GitHub repositories:

  1. mwinda-app: : The front-end code and general notes on data preparation and development.
  2. mwinda-backend: The back-end code the provides the scenario data via a Heroku server.
  3. mwinda-data: Several data sources and pre-processing instructions and scripts.

Please feel free to raise an issue on either repository if you notice a bug or have a feature request. We also welcome code contributions and improvements, but cannot guarantee that all requests will be fulfilled, or that all code contributions will be accepted.


Please contact the Resource Matters team at this email address:

This website was developed by Chris Arderne.