The global and national energy systems techno-economic (GNESTE) database: cost and performance data for electricity generation and storage technologies
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Power sector and energy systems models are widely used to explore the impacts of demographic, socio-economic or policy changes on the cost and emissions of electricity generation. Technology cost and performance data are essential inputs to such models. Despite the ubiquity and importance of these parameters, there is no standardised database which collates the variety of values from across the literature, so modellers must collect them independently each time they populate or update model inputs, leading to duplicated efforts and inconsistencies which can profoundly influence model results. Technology cost and performance varies between countries, regions and over time, meaning that data must be country- or region-specific and frequently updated. Values also vary widely between sources, so obtaining a broad consensus view is critical. Here, we present a database which collates historical, current, and future cost and performance data and assumptions for the six most prominent electricity generation technologies; coal, gas, hydroelectric, nuclear, solar photovoltaic (PV) and wind power, which together accounted for over 92 % of installed generation capacity in 2022. In addition, we provide the same data for utility-scale battery energy storage systems (BESS), regarded as critical to the integration of variable renewables such as wind and solar PV. The data are global in scope but with regional and national specificity, covers the years 2015 through to 2050, and span 5518 datapoints from 56 sources. The database enables modellers to select and justify model input data and provides a benchmark for comparing assumptions and projections to other sources across the literature to validate model inputs and outputs. It is designed to be easily updated with new sources of data, ensuring its utility, comprehensiveness, and broad applicability in future.
Date Issued
2024-08-01
Date Acceptance
2024-06-18
Citation
Data in Brief, 2024, 55
ISSN
2352-3409
Publisher
Elsevier
Journal / Book Title
Data in Brief
Volume
55
Copyright Statement
© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/39234065
PII: S2352-3409(24)00636-X
Subjects
Capital costs
Efficiency
Electricity generation
Electricity storage
Financing costs
Multidisciplinary Sciences
Operating costs
Science & Technology
Science & Technology - Other Topics
Publication Status
Published
Coverage Spatial
Netherlands
Article Number
110669
Date Publish Online
2024-06-25