Africa‘s electricity unlikely to go green this decade
13 Jan 2021 | Source: RWTH Aachen
Researchers from the University of Oxford and RWTH Aachen University have conducted a study on electricity generation across the African continent by 2030. Their findings were published in Nature Energy on January 11, 2021, in an article titled “A machine-learning approach to predicting Africa’s electricity mix based on planned power plants and their chances of success.”
The researchers predict that total electricity generation will double by 2030, with fossil fuels accounting for two-thirds of all generated electricity across Africa. Furthermore, the study shows that the share of non-hydro renewables in African electricity generation is likely to remain below 10 percent in 2030. “The development community and African decision makers need to act quickly if the continent wants to avoid being locked into a carbon-intense energy future,” says Philipp Trotter, study author and researcher at RWTH’s Chair of Operations Management and Oxford’s Smith School.
The study uses a state-of-the art machine-learning technique to analyze the pipeline of over 2,500 currently planned power plants and their chances of being successfully commissioned. The research also highlights regional differences in the pace of the transition to renewables, with Southern Africa leading the way. The country of South Africa alone is forecast to add almost 40 percent of Africa’s total predicted new solar capacity by 2030.
The study suggests that a decisive move towards renewable energy in Africa would require a significant shock to the current system. This includes large-scale cancellation of fossil fuel plants currently being planned.
In addition, the study identifies ways in which planned renewable energy projects can be designed to improve their success chances – for example, smaller size, fitting ownership structure, and availability of development finance.
“There is a prominent narrative in the energy planning community that the continent will be able to take advantage of its vast renewable energy resources and rapidly decreasing clean technology prices to leapfrog to renewables by 2030 – but our analysis shows that overall it is not currently positioned to do so,” explains Galina Alova, study lead author and researcher at the Oxford Smith School of Enterprise and the Environment.
Alova, G., Trotter, P. A., & Money, A. "A machine-learning approach to predicting Africa’s electricity mix based on planned power plants and their chances of success. Nat. Energy" (2021)
Dr. Philipp Trotter
Chair of Operations Management
Telefon: +49 1590 6379882
Oxford Smith School of Enterprise and the Environment