IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v263y2023ipas0360544222024963.html
   My bibliography  Save this article

A statistical approach to modeling the variability between years in renewable infeed on energy system level

Author

Listed:
  • Jahns, Christopher
  • Osinski, Paul
  • Weber, Christoph

Abstract

Energy system models often rely on assumptions about the infeed of renewable energies. Despite their significance, the renewable time series are often based on single weather years, selected without applying clear criteria. For planning purposes of photovoltaic plants or heating and cooling systems, it is common practice to artificially create weather years composed of months from different years. However, there are only few models for the composition of artificial weather years that represent a well-defined high- or low-infeed-scenario. A new method is proposed to artificially construct infeed time series on system level. Under the assumption of a normal distribution, we compose an infeed time series which aims at meeting a certain quantile of annual infeed. Thus, it is possible to construct different infeed scenarios, to model the inter-year variability of the renewable infeed. The method at hand can be useful for everyone who uses exogenous infeed time series in energy modeling.

Suggested Citation

  • Jahns, Christopher & Osinski, Paul & Weber, Christoph, 2023. "A statistical approach to modeling the variability between years in renewable infeed on energy system level," Energy, Elsevier, vol. 263(PA).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pa:s0360544222024963
    DOI: 10.1016/j.energy.2022.125610
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222024963
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125610?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nahmmacher, Paul & Schmid, Eva & Hirth, Lion & Knopf, Brigitte, 2016. "Carpe diem: A novel approach to select representative days for long-term power system modeling," Energy, Elsevier, vol. 112(C), pages 430-442.
    2. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
    3. Jung, Christopher & Schindler, Dirk, 2018. "On the inter-annual variability of wind energy generation – A case study from Germany," Applied Energy, Elsevier, vol. 230(C), pages 845-854.
    4. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    5. Polo, Jesús & Alonso-Abella, Miguel & Martín-Chivelet, Nuria & Alonso-Montesinos, Joaquín & López, Gabriel & Marzo, Aitor & Nofuentes, Gustavo & Vela-Barrionuevo, Nieves, 2020. "Typical Meteorological Year methodologies applied to solar spectral irradiance for PV applications," Energy, Elsevier, vol. 190(C).
    6. Li, Honglian & Yang, Yi & Lv, Kailin & Liu, Jing & Yang, Liu, 2020. "Compare several methods of select typical meteorological year for building energy simulation in China," Energy, Elsevier, vol. 209(C).
    7. Sun, Jingting & Li, Zhengrong & Xiao, Fu & Xiao, Jianzhuang, 2020. "Generation of typical meteorological year for integrated climate based daylight modeling and building energy simulation," Renewable Energy, Elsevier, vol. 160(C), pages 721-729.
    8. Huang, Kuo-Tsang, 2020. "Identifying a suitable hourly solar diffuse fraction model to generate the typical meteorological year for building energy simulation application," Renewable Energy, Elsevier, vol. 157(C), pages 1102-1115.
    9. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    10. Zappa, William & Junginger, Martin & van den Broek, Machteld, 2019. "Is a 100% renewable European power system feasible by 2050?," Applied Energy, Elsevier, vol. 233, pages 1027-1050.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Seljom, Pernille & Lind, Arne & Wagner, Fabian & Mesfun, Sennai, 2020. "Short-term solar and wind variability in long-term energy system models - A European case study," Energy, Elsevier, vol. 209(C).
    2. Zappa, William & Junginger, Martin & van den Broek, Machteld, 2021. "Can liberalised electricity markets support decarbonised portfolios in line with the Paris Agreement? A case study of Central Western Europe," Energy Policy, Elsevier, vol. 149(C).
    3. 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).
    4. Shirizadeh, Behrang & Quirion, Philippe, 2021. "Low-carbon options for the French power sector: What role for renewables, nuclear energy and carbon capture and storage?," Energy Economics, Elsevier, vol. 95(C).
    5. Héctor Marañón-Ledesma & Asgeir Tomasgard, 2019. "Analyzing Demand Response in a Dynamic Capacity Expansion Model for the European Power Market," Energies, MDPI, vol. 12(15), pages 1-24, August.
    6. Tejada-Arango, Diego A. & Wogrin, Sonja & Siddiqui, Afzal S. & Centeno, Efraim, 2019. "Opportunity cost including short-term energy storage in hydrothermal dispatch models using a linked representative periods approach," Energy, Elsevier, vol. 188(C).
    7. Matsuo, Yuhji & Endo, Seiya & Nagatomi, Yu & Shibata, Yoshiaki & Komiyama, Ryoichi & Fujii, Yasumasa, 2020. "Investigating the economics of the power sector under high penetration of variable renewable energies," Applied Energy, Elsevier, vol. 267(C).
    8. Xin-Cheng Meng & Yeon-Ho Seong & Min-Kyu Lee, 2021. "Research Characteristics and Development Trend of Global Low-Carbon Power—Based on Bibliometric Analysis of 1983–2021," Energies, MDPI, vol. 14(16), pages 1-20, August.
    9. Müller, Inga M., 2022. "Energy system modeling with aggregated time series: A profiling approach," Applied Energy, Elsevier, vol. 322(C).
    10. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    11. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    12. Lugovoy, Oleg & Gao, Shuo & Gao, Ji & Jiang, Kejun, 2021. "Feasibility study of China's electric power sector transition to zero emissions by 2050," Energy Economics, Elsevier, vol. 96(C).
    13. Radu, David & Berger, Mathias & Dubois, Antoine & Fonteneau, Raphaël & Pandžić, Hrvoje & Dvorkin, Yury & Louveaux, Quentin & Ernst, Damien, 2022. "Assessing the impact of offshore wind siting strategies on the design of the European power system," Applied Energy, Elsevier, vol. 305(C).
    14. Pavičević, Matija & Mangipinto, Andrea & Nijs, Wouter & Lombardi, Francesco & Kavvadias, Konstantinos & Jiménez Navarro, Juan Pablo & Colombo, Emanuela & Quoilin, Sylvain, 2020. "The potential of sector coupling in future European energy systems: Soft linking between the Dispa-SET and JRC-EU-TIMES models," Applied Energy, Elsevier, vol. 267(C).
    15. Maeder, Mattia & Weiss, Olga & Boulouchos, Konstantinos, 2021. "Assessing the need for flexibility technologies in decarbonized power systems: A new model applied to Central Europe," Applied Energy, Elsevier, vol. 282(PA).
    16. Clemens Gerbaulet & Casimir Lorenz, 2017. "dynELMOD: A Dynamic Investment and Dispatch Model for the Future European Electricity Market," Data Documentation 88, DIW Berlin, German Institute for Economic Research.
    17. Marko Hočevar & Lovrenc Novak & Primož Drešar & Gašper Rak, 2022. "The Status Quo and Future of Hydropower in Slovenia," Energies, MDPI, vol. 15(19), pages 1-13, September.
    18. Lukas Kriechbaum & Philipp Gradl & Romeo Reichenhauser & Thomas Kienberger, 2020. "Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation," Energies, MDPI, vol. 13(15), pages 1-23, July.
    19. Behrang Shirizadeh, Quentin Perrier, and Philippe Quirion, 2022. "How Sensitive are Optimal Fully Renewable Power Systems to Technology Cost Uncertainty?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    20. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:263:y:2023:i:pa:s0360544222024963. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.