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Probabilistic projections of global wind and solar power growth based on historical national experience

  • Avi Jakhmola
  • , Jessica Jewell
  • , Vadim Vinichenko
  • , Aleh Cherp
  • Lund University
  • Chalmers University of Technology
  • University of Bergen
  • International Institute for Applied Systems Analysis, Laxenburg

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

Despite the recent surge of wind and solar power, both technologies need to accelerate to meet climate goals. Yet, there are no robust methods to assess the likelihood of such acceleration. Here we show that renewable energy deployment follows a recurring pattern across countries with prolonged periods of relatively steady growth punctuated by growth pulses. Based on this insight and on observed growth trajectories in early adopting countries, we develop a probabilistic model (PROLONG) for projecting global wind and solar power deployment. In our central projections, both wind and solar power grow similarly to Intergovernmental Panel on Climate Change 2 °C-compatible pathways and faster than in current policy scenarios. The COP28 pledge to triple renewables by 2030 is near the 95th percentile of our projections and requires that the growth of wind and solar photovoltaics in major economies accelerate by 1.4–3 times and 2–5 times, respectively. PROLONG can be adopted for data-driven projections of other policy-dependent energy technologies.
Original languageEnglish
JournalNature Energy
DOIs
StatePublished - 14 Apr 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Energy transitions
  • Renewable energy
  • Cimate change mitigation
  • Technology diffusion
  • Solar PV
  • Wind energy
  • Probabilistic projections

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