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Simulating Annual Variation in Load, Wind, and Solar by Representative Hour Selection

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  • Geoffrey J. Blanford
  • James H. Merrick
  • John E.T. Bistline
  • David T. Young

Abstract

The spatial and temporal variability of renewable generation has important economic implications for electric sector investments and system operations. This study describes a method for selecting representative hours to preserve key distributional requirements for regional load, wind, and solar time series with a two-orders-of-magnitude reduction in dimensionality. We describe the implementation of this procedure in the US-REGEN model and compare impacts on energy system decisions with more common approaches. The results demonstrate how power sector modeling and capacity planning decisions are sensitive to the representation of intra-annual variation and how our proposed approach outperforms simple heuristic selection procedures with lower resolution. The representative hour approach preserves key properties of the joint underlying hourly distributions, whereas seasonal average approaches over-value wind and solar at higher penetration levels and under-value investment in dispatchable capacity by inaccurately capturing the corresponding residual load duration curves.

Suggested Citation

  • Geoffrey J. Blanford & James H. Merrick & John E.T. Bistline & David T. Young, 2018. "Simulating Annual Variation in Load, Wind, and Solar by Representative Hour Selection," The Energy Journal, , vol. 39(3), pages 189-212, May.
  • Handle: RePEc:sae:enejou:v:39:y:2018:i:3:p:189-212
    DOI: 10.5547/01956574.39.3.gbla
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    1. Nelson, James & Johnston, Josiah & Mileva, Ana & Fripp, Matthias & Hoffman, Ian & Petros-Good, Autumn & Blanco, Christian & Kammen, Daniel M., 2012. "High-resolution modeling of the western North American power system demonstrates low-cost and low-carbon futures," Energy Policy, Elsevier, vol. 43(C), pages 436-447.
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    Cited by:

    1. Bistline, John E.T. & Brown, Maxwell & Siddiqui, Sauleh A. & Vaillancourt, Kathleen, 2020. "Electric sector impacts of renewable policy coordination: A multi-model study of the North American energy system," Energy Policy, Elsevier, vol. 145(C).
    2. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
    3. Pavičević, Matija & Kavvadias, Konstantinos & Pukšec, Tomislav & Quoilin, Sylvain, 2019. "Comparison of different model formulations for modelling future power systems with high shares of renewables – The Dispa-SET Balkans model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. John E. T. Bistline & David T. Young, 2022. "The role of natural gas in reaching net-zero emissions in the electric sector," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    5. Teichgraeber, Holger & Lindenmeyer, Constantin P. & Baumgärtner, Nils & Kotzur, Leander & Stolten, Detlef & Robinius, Martin & Bardow, André & Brandt, Adam R., 2020. "Extreme events in time series aggregation: A case study for optimal residential energy supply systems," Applied Energy, Elsevier, vol. 275(C).
    6. Bistline, John E.T. & Blanford, Geoffrey J., 2020. "Value of technology in the U.S. electric power sector: Impacts of full portfolios and technological change on the costs of meeting decarbonization goals," Energy Economics, Elsevier, vol. 86(C).
    7. Li, Francis G.N. & Bataille, Chris & Pye, Steve & O'Sullivan, Aidan, 2019. "Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?," Applied Energy, Elsevier, vol. 239(C), pages 991-1002.
    8. Ken Oshiro & Shinichiro Fujimori, 2024. "Limited impact of hydrogen co-firing on prolonging fossil-based power generation under low emissions scenarios," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    9. Bistline, John E.T. & Merrick, James H., 2020. "Parameterizing open-source energy models: Statistical learning to estimate unknown power plant attributes," Applied Energy, Elsevier, vol. 269(C).
    10. ZareAfifi, Farzan & Mahmud, Zabir & Kurtz, Sarah, 2023. "Diurnal, physics-based strategy for computationally efficient capacity-expansion optimizations for solar-dominated grids," Energy, Elsevier, vol. 279(C).
    11. Merrick, James H. & Bistline, John E.T. & Blanford, Geoffrey J., 2024. "On representation of energy storage in electricity planning models," Energy Economics, Elsevier, vol. 136(C).
    12. Bistline, John E.T. & Young, David T., 2020. "Emissions impacts of future battery storage deployment on regional power systems," Applied Energy, Elsevier, vol. 264(C).
    13. John E. T. Bistline & Geoffrey Blanford & John Grant & Eladio Knipping & David L. McCollum & Uarporn Nopmongcol & Heidi Scarth & Tejas Shah & Greg Yarwood, 2022. "Economy-wide evaluation of CO2 and air quality impacts of electrification in the United States," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    14. Scott, Ian J. & Carvalho, Pedro M.S. & Botterud, Audun & Silva, Carlos A., 2019. "Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. Marcy, Cara & Goforth, Teagan & Nock, Destenie & Brown, Maxwell, 2022. "Comparison of temporal resolution selection approaches in energy systems models," Energy, Elsevier, vol. 251(C).
    16. Bistline, John & Santen, Nidhi & Young, David, 2019. "The economic geography of variable renewable energy and impacts of trade formulations for renewable mandates," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 79-96.
    17. Edmonds, James & Nichols, Christopher & Adamantiades, Misha & Bistline, John & Huster, Jonathan & Iyer, Gokul & Johnson, Nils & Patel, Pralit & Showalter, Sharon & Victor, Nadja & Waldhoff, Stephanie , 2020. "Could congressionally mandated incentives lead to deployment of large-scale CO2 capture, facilities for enhanced oil recovery CO2 markets and geologic CO2 storage?," Energy Policy, Elsevier, vol. 146(C).
    18. Bistline, John & Blanford, Geoffrey & Mai, Trieu & Merrick, James, 2021. "Modeling variable renewable energy and storage in the power sector," Energy Policy, Elsevier, vol. 156(C).
    19. Mai, Trieu & Bistline, John & Sun, Yinong & Cole, Wesley & Marcy, Cara & Namovicz, Chris & Young, David, 2018. "The role of input assumptions and model structures in projections of variable renewable energy: A multi-model perspective of the U.S. electricity system," Energy Economics, Elsevier, vol. 76(C), pages 313-324.
    20. Merrick, James H. & Weyant, John P., 2019. "On choosing the resolution of normative models," European Journal of Operational Research, Elsevier, vol. 279(2), pages 511-523.
    21. Mallapragada, Dharik S. & Sepulveda, Nestor A. & Jenkins, Jesse D., 2020. "Long-run system value of battery energy storage in future grids with increasing wind and solar generation," Applied Energy, Elsevier, vol. 275(C).
    22. John E. T. Bistline & James Merrick & Victor Niemeyer, 2020. "Estimating Power Sector Leakage Risks and Provincial Impacts of Canadian Carbon Pricing," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(1), pages 91-118, May.

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    More about this item

    Keywords

    Renewables; Variability; Capacity Planning; Power System; Modeling; Market Integration; Representative Hours;
    All these keywords.

    JEL classification:

    • F0 - International Economics - - General

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