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Planning reliable wind- and solar-based electricity systems

Lookup NU author(s): Dr Hannah BloomfieldORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Resource adequacy, or ensuring that electricity supply reliably meets demand, is more challenging for wind- and solar-based electricity systems than fossil-fuel-based ones. Here, we investigate how the number of years of past weather data used in designing least-cost systems relying on wind, solar, and energy storage affects resource adequacy. We find that nearly 40 years of weather data are required to plan highly reliable systems (e.g., zero lost load over a decade). In comparison, this same adequacy could be attained with 15 years of weather data when additionally allowing traditional dispatchable generation to supply 5 % of electricity demand. We further observe that the marginal cost of improving resource adequacy increased as more years, and thus more weather variability, were considered for planning. Our results suggest that ensuring the reliability of wind- and solar-based systems will require using considerably more weather data in system planning than is the current practice. However, when considering the potential costs associated with unmet electricity demand, fewer planning years may suffice to balance costs against operational reliability.


Publication metadata

Author(s): Ruggles TH, Virguez E, Reich N, Dowling J, Bloomfield HC, Antonini EGA, Davis SJ, Lewis NS, Caldeira K

Publication type: Article

Publication status: Published

Journal: Advances in Applied Energy

Year: 2024

Volume: 15

Online publication date: 10/08/2024

Acceptance date: 03/08/2024

Date deposited: 27/08/2024

ISSN (electronic): 2666-7924

Publisher: Elsevier

URL: https://doi.org/10.1016/j.adapen.2024.100185

DOI: 10.1016/j.adapen.2024.100185

Data Access Statement: All model code, input data, and analysis results are publicly available and documented at: https://github.com/Carnegie/MEM_public/tree/Ruggles_et_al_2024


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