Energy Transition During Energy Crisis: Cape Town's Experience (2025-2026)

Background

At the 26th Conference of Parties (COP26) in Glasgow, the government of South Africa made a historic commitment with a multi-government International Partners Group to create the first Just Energy Transition Partnership (JETP). The South Africa JETP is meant to grapple with the unique challenges of decarbonizing South Africa's fossil fuel-dependent economy. The commitment of the partners to enable a “just transition” is the distinguishing feature of the JETP, which recognizes the direct and indirect impact that energy transition has on livelihoods, workers and communities. The International Partners Group pledged $8.5 billion U.S. dollars over the initial period to support the realization of a low-carbon future in line with South Africa's most ambitious Nationally Determined Contribution commitments.

Meanwhile, South Africa is grappling with an unprecedented and worsening power crisis, brought on by a complex combination of aging infrastructure, poor maintenance and governance, criminal corruption and unprecedented levels of demand. The consequence has been regular, widespread load-shedding (i.e., power outages or redistribution to relieve stress on energy sources) that harms productivity, decreases household well-being and has contributed to capital flight and deindustrialization. This situation creates substantial risk and opportunity for the decarbonization agenda. Many incorrectly perceive that energy transition is contributing to the crisis, even as the shift to renewable energy generation is accelerating. Whether JETP opportunities are sufficient and justly distributed remains an open question.

Project Description

Building on the work of a previous team, this project team will seek to understand the justice implications of energy transition during energy crisis as experienced in Cape Town, South Africa. Cape Town is a microcosm for the wider inequalities facing the country with a wide gulf separating wealthy and impoverished areas. These play out in a dramatic way as households and firms in the former areas move quickly to adopt rooftop solar to cope, incentivized by net metering, even as many low-income townships bear heavier load-shedding burdens and cannot make the same upfront investments.

Project team members will document unequal burdens by coupling new data analytics and modeling approaches, propose policy solutions that might decrease energy poverty inequalities and support JETP-related decision-making, and leverage the tools developed to evaluate the distributional impacts of these solutions.

In 2025-2026, team members will continue work to detect distributed solar generation capacity in Cape Town using deep-learning processing of aerial imagery. The team will use information gathered from the previous team to increase model accuracy and set up other analyses. Team members will use aerial imagery data to evaluate the implications of recently introduced tax incentives on the adoption of home solar systems. Aerial imagery data will also be used to evaluate the potential loss of income to Eskom, South Africa’s largest electric power utility, due to decreased purchased electricity consumption from households with home solar systems. Team members will evaluate how revenue loss may affect Eskom’s ability to invest in infrastructure and provide subsidized electricity to low-income households.

Team members will learn about the policy context of the energy crisis in South Africa and the global rationale for JETP projects, engaging with researchers and guest speakers from South Africa. Subteams will work on the energy systems and econometric modeling components. Team members working on energy systems will incorporate new distributed generation potential into the energy systems models to understand its implications for meeting energy demands from the grid, and for considering policy solutions. Students working on econometric modeling will carry out econometric analysis of energy use patterns in the context of distributed solar generation adoption amid time-varying load-shedding to inform the modeling.

Anticipated Outputs

Deep-learning model for home solar identification; econometric models, a prediction model and a dataset on home solar system adoption; a scenario analysis energy model for Cape Town; research presentation

Student Opportunities

Ideally, this project team will include 5 graduate students and 5 undergraduate students interested in data science, statistics, engineering, modeling, environmental policy, economics, political economy, sociology and/or applied social science.

Students will learn how to integrate and leverage the capabilities of different types of energy and infrastructure modeling to pursue a coherent research design and agenda. Team members will think critically about the strengths and limitations of different approaches and will learn general energy system modeling and coding and build skills in empirical applications of economics. Team members will apply these skills to model an optimal energy system that informs econometric modeling. The team will consider the relationship between electricity access and inequality and potential policy solutions that take both into consideration.

In Fall 2025, the team will meet on Fridays from 10-11:20 a.m.

See also the related Data+ project for Summer 2025; there is a separate application process for students who are interested in this optional summer component.

Timing

Summer 2025 – Spring 2026

• Summer 2025 (optional): Improve deep-learning algorithm for detection of solar home systems, other solar panel installations and solar water heaters in Cape Town
• Fall 2025: Learn about the South Africa energy crisis; design survey; conduct econometric analysis; model energy systems; conduct deep-learning aerial detection; seek IEB approval if necessary
• Spring 2026: Analyze survey, models and aerial detection; develop project summary outputs

Crediting

Academic credit available for fall and spring semesters; summer funding available

See related Data+ summer project, Energy Transition During Energy Crisis: Cape Town's Experience (2025); see earlier related team Energy Transition During Energy Crisis: Cape Town’s Experience (2024-2025).