Clean technology cost projections: investment and levelized costs of solar, wind, battery, and hydrogen

Reliable cost projection data is critical for energy system modelling, guiding policy and investment decisions that underpin the global energy transition. In this work, we compile and standardise a broad dataset from over 110 existing regional and global studies to provide an organised and spatio-temporally granular dataset of cost projections for major clean energy technologies. The dataset covers Capital Expenditures (CAPEX) and Levelised Costs of Electricity or Hydrogen (LCOE or LCOH) for utility-scale and rooftop photovoltaics, onshore and offshore wind power, grid-scale Li-ion batteries, concentrated solar thermal power, and large-scale alkaline and PEM electrolysers. The data span national, continental, and global scales, with annual granularity through 2050 and metadata for source type and region. Values under various scenarios are provided to enable risk and uncertainty assessments. This resource supports scenario modelling, investment planning, policy design, and benchmarking in the context of decarbonisation pathways. While the data are drawn entirely from existing sources, the novelty lies in the structured harmonisation, metadata processing, and comprehensive coverage, making it suitable for techno-economic evaluation and robust energy system modelling.

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Publication Details

Journal
Scientific Data
Published
2025-10-22
DOI
https://doi.org/10.1038/s41597-025-05951-4
Citations
2
Primary Topic
Global Energy and Sustainability Research
Type
article
Field-Weighted Citation Impact
0.73
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Clean technology cost projections: investment and levelized costs of solar, wind, battery, and hydrogen

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2 citations
Scientific Data
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article

Clean technology cost projections: investment and levelized costs of solar, wind, battery, and hydrogen

Hadi Vatankhah Ghadim, Philip Odonkor, Hans Christian Gils, Rebecca Peer, Jannik Haas, Christian Breyer, E. Grant Read, Mengzhu Xiao
article en
2 citations

Abstract

Reliable cost projection data is critical for energy system modelling, guiding policy and investment decisions that underpin the global energy transition. In this work, we compile and standardise a broad dataset from over 110 existing regional and global studies to provide an organised and spatio-temporally granular dataset of cost projections for major clean energy technologies. The dataset covers Capital Expenditures (CAPEX) and Levelised Costs of Electricity or Hydrogen (LCOE or LCOH) for utility-scale and rooftop photovoltaics, onshore and offshore wind power, grid-scale Li-ion batteries, concentrated solar thermal power, and large-scale alkaline and PEM electrolysers. The data span national, continental, and global scales, with annual granularity through 2050 and metadata for source type and region. Values under various scenarios are provided to enable risk and uncertainty assessments. This resource supports scenario modelling, investment planning, policy design, and benchmarking in the context of decarbonisation pathways. While the data are drawn entirely from existing sources, the novelty lies in the structured harmonisation, metadata processing, and comprehensive coverage, making it suitable for techno-economic evaluation and robust energy system modelling.

Scientific DataVol. 12(1)
Stevens Institute of Technology (US), University of Canterbury (NZ), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), International Renewable Energy Agency (AE), Lappeenranta-Lahti University of Technology (FI)
Openalex Percentile: Top 27%
Global Energy and Sustainability Research
0.73
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