Kenya is among the top 20 countries with the largest energy access deficits; 12 million of its citizens are still living without electricity[1]. In 2021, over 75% of the population was cooking with polluting fuels like charcoal, coal, crop waste, dung, kerosene or wood,[2] which pose serious health, environmental and socio-economic challenges. Access to finance, affordability of clean technologies and fuels as well as underdeveloped infrastructure for technologies and fuel distribution hamper an increased uptake of clean cooking in Kenya.
Lack of granular data to inform the most strategic interventions is another big barrier. The Energy Access Explorer (EAE) is helping in addressing this challenge while contributing to initiatives to bring cleaner cooking alternatives to Kenya.
Bringing Energy Access Explorer to Kenya to Advance Clean Cooking Goals
Currently available in eight countries in Africa and Asia, EAE is an online, open-source, interactive platform that enables clean energy players to identify high priority areas for energy interventions. In Kenya, EAE is used to inform the design of subnational County Energy Plans as mandated by the Energy Act 2019. At National level, EAE supports the upcoming Kenya National Clean Cooking and e-Cooking Strategies. To enhance usability of EAE for clean cooking, WRI — in partnership with the Clean Cooking Alliance (CCA), the Ministry of Energy and Petroleum (MoEP), Clean Cooking Association of Kenya (CCAK), Royal Institute of Technology, Kartoza and other stakeholders — are building on the existing EAE infrastructure to add data and use cases focusing specifically on the adoption of clean cooking.
While EAE can be used to identify where the expansion of energy shall be prioritized, two other open-source modeling algorithms (OnStove and OnSSET) have been developed to estimate (a) costs and benefits associated to different cooking solutions and (b) the reach and type of electrification technologies in the studied area. This way, EAE users can answer two questions: What technologies to invest in? Where to prioritize certain interventions based on multiple criteria?
OnStove is a geospatial clean cooking tool used to determine the net-benefit of cooking with different stoves. OnStove compares fuel-technology options for providing cooking access to answer questions like: Which fuel-technology combinations provide the highest net benefits across a country or region?
The Open-Source Spatial Electrification Tool (OnSSET) is also a geospatial based optimization tool developed to support least-cost electrification planning and decision-making to further energy access goals in currently unserved locations.
In August 2023, WRI, CCA, KTH and CCAK organized a workshop which brought together stakeholders from the government, clean cooking associations and enterprises, development institutions and research organizations. The main objective was to ensure that EAE Kenya is applicable to the local contexts and to synergize with other clean cooking initiatives going on in the country.
Identifying Priority Areas for Clean Cooking Interventions
Two scenarios were analyzed to inform the forthcoming Kenya National e-Cooking Strategy being developed by Nuvoni Research and partners:
- Financial assistance strategies such as cooking appliance subsidies or credit financing to target households willing to transition, but without the resources to purchase the e-cooking devices. The EAE was used to show the locations of populations that meet these criteria.
- Behavioral change campaigns targeting households with the resources (both financial and infrastructural) to transition to clean cooking, but who are not willing to transition.
Scenario 1: Households willing to transition to e-cooking and are above tier 3, but have poor wealth index
For this scenario, the EAE was used to locate households willing to transition to e-cooking (using survey data). The analysis also showed which of these households are above tier 3 of electricity access, meaning they are in areas with good grid infrastructure and a reliable energy supply (receive more than 8hrs of electricity per day). From the remaining areas that meet the first two criteria, the analysis further narrowed the search to highlight the populations with low wealth index (below middle-class), with inputs derived from the primary surveys. These households were then flagged as those that could be targeted for financial assistance strategies, such as cooking appliance subsidies or credit financing.
Datasets added to EAE for this scenario, plus filters used in the analysis:
| Data | Filter |
|---|---|
| Population Density | |
| Households Willing to Transition | Counties with 50% and above households willing to transition to e-cooking |
| Wealth Index | Counties with 50% and above households in the poor, lower-middle class, and middle-class wealth index. |
| Overall, Tier (3-5) | Households above overall tier 3 |
The above datasets were loaded to the EAE and filtered as specified in the table above.
Scenario 1 Results
From this analysis, we found that a total of 21.2 people meet these criteria across the entire country, with a majority located in the western, central and southeastern parts of Kenya, as highlighted in the map above.
The tool also assigns an energy access potential index to these populations to illustrate which of them have the highest to lowest potential for targeting based on how best they meet the criteria. (Areas with higher populations, more households willing to transition, and more electricity access generally score higher in this index. The map assigns brighter colors to these areas with higher energy access potential index).
Scenario 2: Households not willing to transition to e-cooking, above tier 3, but have high wealth index
The EAE was used to show locations of households unwilling to transition to e-cooking, based on survey data. The analysis also narrowed down to show of these households, which are above tier 3 of electricity access. From the remaining areas that meet the first two criteria, the analysis then scaled down to highlight the populations with high wealth index (above the middle-class) with inputs derived from primary surveys. These households were then flagged as those that could be targeted for behavioral change campaigns.
Datasets added plus filters:
| Data | Filter |
|---|---|
| Population Density | |
| Households not Willing to Transition | Counties with 30% and above households not willing to transition to e-cooking |
| Wealth Index | Counties with 30% and above households in the upper middle class, and wealthy index. |
| Overall, Tier (3-5) | Households above overall tier 3 |
The above datasets were loaded to the EAE and filtered as specified in the table above.
Scenario 2 Results
From this analysis, we found that a total of 9.8 million people meet these criteria across the entire country, with a majority of them located in the western, southwestern and southern parts of Kenya, as highlighted in the map above.
The tool also assigns an energy access potential index to these populations to illustrate which of them have the highest to lowest potential for targeting, based on how best they meet the standards. Areas with higher populations above the middle-class index, more households unwilling to transition, and more proximity to electricity access generally score higher, could be targeted first for behavioral change campaigns. The map assigns brighter colors to these areas with higher energy access potential.
Moving Forward
WRI and partners plan to conduct capacity-building workshops on EAE quarterly in Kenya. So far, two workshops have been conducted to support EAE’s use in advancing Kenya’s clean cooking agenda.
Workshop participants proposed formation of a cross-sectoral EAE Data Working Group, which shall be responsible for sharing data in a standardized format and updating it in the EAE.
As the EAE Data Working Group moves forward with these action items, we will continue broad stakeholder collaboration and capacity-building initiatives to support Kenya’s National Clean Cooking and e-Cooking Strategies. To learn more about the use of EAE in Kenya, please contact Douglas Ronoh: douglas.ronoh@wri.org.
[1] sdg7-report2023-full_report.pdf (esmap.org)
[2] Kenya | Tracking SDG 7 (esmap.org)
