Geophysical constraints on the reliability of solar and wind power worldwide
Abstract
If future net-zero emissions energy systems rely heavily on solar and wind resources, spatial and temporal mismatches between resource availability and electricity demand may challenge system reliability. Using 39 years of hourly reanalysis data (1980–2018), we analyze the ability of solar and wind resources to meet electricity demand in 42 countries, varying the hypothetical scale and mix of renewable generation as well as energy storage capacity. Assuming perfect transmission and annual generation equal to annual demand, but no energy storage, we find the most reliable renewable electricity systems are wind-heavy and satisfy countries' electricity demand in 72–91% of hours (83–94% by adding 12 h of storage). Yet even in systems which meet >90% of demand, hundreds of hours of unmet demand may occur annually. Our analysis helps quantify the power, energy, and utilization rates of additional energy storage, demand management, or curtailment, as well as the benefits of regional aggregation.
Additional Information
© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received 24 February 2021; Accepted 24 September 2021; Published 22 October 2021. This work was supported by the National Natural Science Foundation of China (41921005). D.T., D.J.F., L.D., and K.C. were supported by the Carnegie Institution for Science endowment and a gift from Gates Ventures, Inc. S.J.D. was supported by the US National Science Foundation (Innovations at the Nexus of Food, Energy and Water Systems (INFEWS) grant EAR 1639318). Data availability: The electricity demand, solar, and wind capacity factors data generated for this study have been deposited in Dantong2021/Geophysical_constraints: Data of electricity demand, solar and wind capacity factors (v1.0). Zenodo. https://doi.org/10.5281/zenodo.5463202. Code availability: The Macro Electricity Model (MEM) code is available on GitHub via https://github.com/ClabEnergyProject/MEM. Author Contributions: K.C., N.S.L., S.J.D., and D.T. designed the study. D.T. performed the analyses, with support from D.J.F. on simulations and L.D. on resources estimates, and from S.J.D., Q.Z., N.S.L., and K.C. on analytical approaches. D.T. and S.J.D. led the writing with input from all coauthors. The authors declare no competing interests. Peer review information: Nature Communications thanks Jesse Jenkin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.Attached Files
Published - s41467-021-26355-z.pdf
Supplemental Material - 41467_2021_26355_MOESM1_ESM.pdf
Supplemental Material - 41467_2021_26355_MOESM2_ESM.pdf
Supplemental Material - 41467_2021_26355_MOESM3_ESM.pdf
Supplemental Material - 41467_2021_26355_MOESM4_ESM.xlsx
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Supplemental Material - 41467_2021_26355_MOESM8_ESM.xlsx
Supplemental Material - 41467_2021_26355_MOESM9_ESM.xlsx
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Additional details
- PMCID
- PMC8536784
- Eprint ID
- 111670
- Resolver ID
- CaltechAUTHORS:20211028-165534518
- National Natural Science Foundation of China
- 41921005
- Carnegie Institution
- Gates Ventures, Inc.
- NSF
- EAR-1639318
- Created
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2021-10-28Created from EPrint's datestamp field
- Updated
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2021-11-22Created from EPrint's last_modified field