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

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 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.

Authors

Institutions

Publication Details

Journal
Nature Energy
Published
2026-04-14
DOI
https://doi.org/10.1038/s41560-026-02021-w
Primary Topic
Global Energy and Sustainability Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Vadim Vinichenko, Avi Jakhmola, Jessica Jewell, Aleh Cherp
Nature Energy
Global Energy and Sustainability Research
article

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

Vadim Vinichenko, Avi Jakhmola, Jessica Jewell, Aleh Cherp
article en

Abstract

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 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.

Nature Energy
International Institute for Applied Systems Analysis (AT), Lund University (SE), Central European University (AT), University of Bergen (NO), Chalmers University of Technology (SE), Research Institute of Industrial Economics (SE)
Climate action
Openalex Percentile: Top 23%
Global Energy and Sustainability Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.