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

Jakhmola, Avi ; Jewell, Jessica ; Vinichenko, Vadim LU and Cherp, Aleh LU orcid (2026) In Nature Energy 11(5). p.743-755
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Energy
volume
11
issue
5
pages
13 pages
publisher
Nature Publishing Group
external identifiers
  • pmid:42221601
ISSN
2058-7546
DOI
10.1038/s41560-026-02021-w
language
English
LU publication?
yes
additional info
© The Author(s) 2026, modified publication 2026.
id
e4fc4768-a368-4306-bc59-42ca15a91c37
date added to LUP
2026-07-09 17:42:15
date last changed
2026-07-10 10:35:12
@article{e4fc4768-a368-4306-bc59-42ca15a91c37,
  abstract     = {{<p>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.</p>}},
  author       = {{Jakhmola, Avi and Jewell, Jessica and Vinichenko, Vadim and Cherp, Aleh}},
  issn         = {{2058-7546}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{743--755}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Energy}},
  title        = {{Probabilistic projections of global wind and solar power growth based on historical national experience}},
  url          = {{http://dx.doi.org/10.1038/s41560-026-02021-w}},
  doi          = {{10.1038/s41560-026-02021-w}},
  volume       = {{11}},
  year         = {{2026}},
}