Database of up-to-date probabilistic technology cost forecasts

This repository contains a database of up-to-date probabilistic technology cost forecasts for key low-carbon and clean energy technologies, developed as part of the Deliverable D3.2 of the PRISMA project. A few different technology cost forecasting methods are applied, and salient methodological issues are discussed, in order to stimulate progress on how energy system models (ESM) and integrated assessment models (IAM) represent technological change and its uncertainty.  The database includes: •    Up-to-date probabilistic technology cost forecasts for solar photovoltaics, onshore and offshore wind energy, lithium-ion batteries, PEM electrolyzers, and LED lighting.•    Model forecasts for lithium-ion battery packs and fuel cell systems used in commercial road freight vehicles.•    Technology cost forecasts for three types of direct air carbon capture and storage (DACCS) constructed using a variation in inherent technology characteristics.•    New learning rate estimate for geothermal energy. Associated report describes the database; outlines the key issues with the reliability of existing deterministic technology cost forecasts and forecasting methodologies; describes recent cost forecasting methodologies that address these issues from various perspectives and how these methodologies are applied to generate technology cost forecasts included in the database; visualizes these forecasts as data plots; and briefly describes key potential uses and limitations of these forecasts.  Please note that the database is embargoed until 1 January 2026 and preliminary access can only be granted for project review purposes. For any questions, please contact the authors.