Accelerating the energy transition in Sub-Saharan Africa: A stochastic programming framework
サブサハラアフリカにおけるエネルギー転換の促進：確率計画フレームワーク (AI 翻訳)
Michael Obeng, Emmanuel Asuming Frimpong, Bernard Aboagye
🤖 gxceed AI 要約
日本語
本研究は、サブサハラアフリカにおける再生可能エネルギー容量拡大を加速するための確率計画フレームワークを提案し、ガーナをケーススタディとする。変動型再生可能エネルギーと水力発電の不確実性をモデル化し、非水力再生可能エネルギー容量が2028年の255.3MWから2060年には8603.3MWに拡大し、年間投資額はGDPの0.06%-1.04%、発電コストは90%以上減少することを示す。これにより、気候目標に整合した加速的なエネルギー転換の実現可能性が示される。
English
This study proposes a stochastic programming framework for accelerating renewable energy capacity expansion in Sub-Saharan Africa, using Ghana as a case study. It models uncertainties in variable renewables and hydro, finding that non-hydro RE capacity will expand from 255.3 MW to 8603.3 MW by 2060, with annual investment costs of 0.06-1.04% of GDP and electricity generation costs decreasing by over 90%. This demonstrates the feasibility of an accelerated energy transition aligned with climate goals.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本論文はガーナを事例に、変動性再生可能エネルギーと水力発電の不確実性を考慮した確率計画フレームワークを提案しており、日本の電力系統計画や途上国支援策にも示唆を与える。
In the global GX context
This paper provides a quantitative decision-support framework for accelerating renewable energy expansion in developing countries, with policy-relevant cost and investment projections. It complements global energy transition literature with a Sub-Saharan African case study.
👥 読者別の含意
🔬研究者:Stochastic programming methodology for energy planning under uncertainty.
🏢実務担当者:Investment cost projections and capacity expansion timeline for renewable projects.
🏛政策担当者:Cost-effective pathways to meet climate goals while ensuring electricity demand.
📄 Abstract（原文）
The increasing frequency and intensity of climate-induced disasters have provided the impetus to limit global temperature rise to 1.5 degrees Celsius, a threshold identified for avoiding the catastrophic effects of climate change. While developed economies have seen increased renewable energy deployments, the slow progress in developing countries creates a significant gap in the global effort to limit global temperature rise. This study proposes a long-term decision-support framework for accelerating RE capacity expansion in sub-Saharan Africa. It employs probabilistic models to address the uncertainties and variabilities in VREs and reservoir-based hydro dams and determines cost-effective strategies that fulfill current and future electricity demands, using Ghana as a case study. Numerical results show that Ghana’s non-hydro RE (NRE) capacity will expand by more than five times from 255.3 MW in 2028 to 8,603.3 MW in 2060. The discounted annual investment required for the new capacity additions ranges from 0.06% to 1.04% of Ghana’s gross domestic product (GDP). Annual electricity generation costs will decrease by more than 90%, from $158/MWh in 2028 to $10/MWh in 2060, due to increased generation from NRE sources. The findings demonstrate that Ghana can achieve an accelerated energy transition consistent with climate objectives while meeting future electricity demand.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.rset.2026.100156first seen 2026-07-13 04:49:25
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