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Comparison of temporal resolution selection approaches in energy systems models

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  • Marcy, Cara
  • Goforth, Teagan
  • Nock, Destenie
  • Brown, Maxwell

Abstract

Capacity expansion models for the power sector are used to project future decisions over the coming decades by simulating investment and operation decisions for the use of electricity. Due to model performance constraints, these models typically do not explicitly simulate every hour within a year, but instead simulate representative time segments (groups of hours). This paper evaluates different approaches for selecting time segments across three methods: sequential, categorical, and clustering, across a wide range of time-segment quantities, for a total of 204 temporal profiles. To measure the performance of each profile's ability to accurately represent data, the root-mean-square-error of each profile's time segments are compared to the data's original hourly data. The temporal alignment across regions is also measured (i.e., how often windy days align across regions). Different spatial resolutions were applied for a subset of the temporal selection methods to investigate the impact spatial resolution has on performance. This paper provides a framework for measuring the value of different temporal selection methods and of adding more granular data to energy system models. Overall, multi-criteria clustering yields the lowest root-mean-square-error across all datasets evaluated and provides a holistic view of the intertwined relationships between renewable generation and electricity demand.

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  • Marcy, Cara & Goforth, Teagan & Nock, Destenie & Brown, Maxwell, 2022. "Comparison of temporal resolution selection approaches in energy systems models," Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:energy:v:251:y:2022:i:c:s0360544222008726
    DOI: 10.1016/j.energy.2022.123969
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    2. Teagan Goforth & Destenie Nock, 2022. "Air pollution disparities and equality assessments of US national decarbonization strategies," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Seljom, Pernille & Rosenberg, Eva & Haaskjold, Kristina, 2024. "The effect and value of end-use flexibility in the low-carbon transition of the energy system," Energy, Elsevier, vol. 292(C).
    4. Wen, Xin & Heinisch, Verena & Müller, Jonas & Sasse, Jan-Philipp & Trutnevyte, Evelina, 2023. "Comparison of statistical and optimization models for projecting future PV installations at a sub-national scale," Energy, Elsevier, vol. 285(C).

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