Hydropower capacity expansion in the African continent under different socio-economic & climate policy scenarios

Hydropower and other renewable energy sources are experiencing new investments for capacityexpansion to provide clean and accessible energy to a growing population in many world areas. Asmost of the untapped hydropower potential lies in developing countries, here, strategic damplanning is critical in supporting the design of capacity expansion with reduced impact oninterconnected water, food, and climate systems. This is true especially for Africa, where more than 300 new hydropower projects are underconsideration, and future population growth projections and associated energy, water, and fooddemands are highly uncertain. In this work, we investigate how to strategically plan hydropower capacity expansion at the Africancontinental scale, providing an estimate of future hydropower capacity needs. Specifically, wemodel the energy system using The Electricity Base Model for Africa (TEMBA), based on theOSeMOSYS energy modelling framework, and we consider capacity factors for each hydropowerproject reported in the African Hydropower Atlas as derived from the hydrologic simulation of theSWAT model that accounts for irrigation demand. To explore different socio-economic and climatepolicy projections, we also downscale final energy demands projections at the country level fromthe SSP database. We then investigate two different planning approaches: first, using scenarioanalysis, we examine how the different individual projections influence hydropower and powersystem development; second, we adopt a two-stage robust optimization methodology to developa robust capacity expansion plan common for all the socio-economic and climate policy scenariosuntil 2035. Finally, we hypothesize that uncertainty about the socio-economic scenario is resolved,and we model the adaptation of the capacity expansion strategy to each of the narrativesconsidered in the period 2035-2050 by solving a new optimization problem. Our results show that not all the 100 GW of hydropower projects considered in the AfricanHydropower Atlas are needed to satisfy the final energy demands. Furthermore, as we observelarge variability in hydropower capacity expansion under different socio-economic projections, weproduce a short-term robust plan extracting the most relevant hydroelectric projects via robustoptimization. Finally, we show that adapting capacity planning decisions based on newinformation can strongly reduce the price of robustness. Our work proposes a methodology for taking planning decisions in an integrated assessmentcontext where scenarios are used to link different societal sectors and resources. When theuncertainty spanned by plausible future states of the world is large and diverging, a combinationof robust optimization and adaptive planning can reduce the potential for bad societal outcomes