Publications
Full list of publications:
June Lukuyu: Google Scholar​​​​
Select Publications
Grid connections and inequitable access to electricity in African cities
Jessica Kersey, Civian Kiki Massa, June Lukuyu, Judith Mbabazi, Jay Taneja, Daniel M Kammen and Veronica Jacome
As the Global South rapidly and inequitably urbanizes, cities are at the forefront of efforts to address energy-related dimensions of poverty. In many African cities, electricity via a connection to a grid—the gold standard of electrification—has not substantially displaced smoky, polluting fuels. Among low-income communities, connections tend to be based on improvised, informal arrangements with local intermediaries. The nature and level of access these connections provide is not well understood and cannot be easily measured using existing energy access metrics such as the Multi-Tier Framework. This study provides a grounded, empirical analysis of grid connections across 25 informal settlements in the Ugandan capital city of Kampala. Using a mixed-methods approach that incorporates surveys, interviews and remote power quality monitoring, we trace electrical and financial flows between the utility, supply intermediaries and end users. We identify 29 unique configurations of these flows—which we term service arrangements—that provide electricity of varying and overall limited levels of affordability, reliability, voltage stability, precarity, autonomy and safety. Our evidence suggests that the grid delivers highly inequitable electricity services that fall short of aspirations of modern energy for the city’s most vulnerable communities.
Managing grid impacts from increased electric vehicle adoption in African cities
June Lukuyu, Rebekah Shirley, and Jay Taneja
Electric vehicles are pivotal for global climate solutions, particularly in emerging markets like Africa. Despite the continent’s clean energy potential, electric vehicle adoption faces unique challenges due to inefficiencies and reliability issues of distribution power grids. Here, we analyze the impacts of expanding electric vehicle fleets—private, commercial, and paratransit—on Nairobi’s power grid. We simulate traffic patterns, charging behaviors, and transformer utilization using local mobility data. Our results show that while electric commercial and paratransit fleets may improve power system efficiency, widespread private EV adoption could significantly strain the grid, increasing peak loads and transformer aging. Smart charging strategies could mitigate these issues, reducing potential transformer replacement costs by up to 40%. Our study highlights the importance of tailored demand management and infrastructure planning to support EV growth in African cities, providing critical insights for policymakers, utilities, and transport planners to facilitate sustainable electric mobility transitions.
Assessing Household Cooking Energy Behavior and Potential for Transition to E-Cooking in Informal Urban Settlements.
Vongai Mutatu, Vijai Modi and June Lukuyu
Traditional cooking methods are hazardous and time-consuming, disproportionately exposing women and girls to these negative effects. In rural areas, fuelwood can be gathered from personal trees or the surrounding landscape. However, urban areas lack the luxury of gathering their biomass, and commercial fuels such as LPG are expensive due to high upfront costs and lumpy recurrent payments. While higher-income households can overcome these barriers, those in dense urban informal settlements find themselves in a precarious situation. Measures to drive E-cooking adoption have the greatest potential to succeed in urban informal settlements because a) access to biomass is constrained, b) most consumers are connected to the grid, and c) living quarters are smaller and lack ventilation. Since informal settlements can make up a significant proportion of the urban population, investing in the transition to clean cooking in these areas may yield the highest returns on public investments.
A Principled Incentive Mechanism to Promote Economic Viability of Mini-Grids
Anokhi Mehta, Luyao Niu, Dinuka Sahabandu, June Lukuyu, and Radha Poovendran
The urgent need for universal electrification and the high cost of grid expansion highlight the crucial role of mini-grids in Sub-Saharan Africa (SSA). These systems harness technologies such as cost-effective renewable energy to provide reliable and affordable electricity to remote, off-grid communities. However, the existing mini-grids lack economic viability in the long run. To address this challenge, mini-grid demand stimulation programs have been developed to stimulate electricity demand by incentivizing the adoption of appliances, particularly for productive purposes. At present, however, there exists no principled analysis to evaluate how incentives for appliance adoption could be structured to benefit customers while contributing to the economic viability of mini-grids. In this paper, we develop a principled incentive mechanism to enhance the economic viability of mini-grids in SSA by stimulating the productive use of electricity. The mini-grid developer offers a range of appliances for rent at affordable rates and competitive electricity pricing to stimulate electricity demand from customers. The customers determine which appliances to rent based on the prices announced by the developer and the utility associated with the appliances. We formulate an optimization problem for the customers and mini-grid developers. Leveraging the formulated problem, we show that customers with limited computational resources can efficiently determine the appliances to rent. We further develop an algorithm for the developer to estimate how the customers will react to the electricity price and rental prices, enabling efficient calculation of both price signals. We show that the proposed approach leads to a win-win situation between the developer and customers. Customers create non-negative profits by adopting productive use appliances, and the developer stimulates the electricity demand which is better aligned with the renewable energy generation. We evaluate the proposed approach using a rural village with ten appliances whose load profiles are obtained from a real-world dataset.