IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v236y2021ics0360544221016571.html
   My bibliography  Save this article

Evaluation of open photovoltaic and wind production time series for Norwegian locations

Author

Listed:
  • Muñoz Ortiz, Miguel
  • Kvalbein, Lisa
  • Hellemo, Lars

Abstract

We investigate the accuracy of wind and photovoltaic time series in individual systems in Norway. To study the accuracy of the available open data sets, we compare the measured production from individual photovoltaic- and wind power plants to the open time series from Renewables.ninja and EMHIRES. Additionally, we try to adjust the wind speed based on the average wind speed from Global Wind Atlas 3.0 and Norwegian water resources and energy directorate's Wind Map to try to achieve more accurate wind speed time series that take into account the local wind conditions, since they are not well represented in the large resolution of the MERRA-2 data set used by Renewables.ninja. The results for photovoltaic production time series are promising, the correlation between production obtained from Renewables.ninja and measured production is above 0.72 and maximum capacity factor difference of 2.5%. For the case of wind production, production time series show considerable deviations depending on the specific wind farm (correlation between 0.51 and 0.91 depending on the case and year). Additionally, the adjustments only improve the time series in some of the wind farms, whereas in others the results are even less accurate than the Renewables.ninja time series compared to the measured data.

Suggested Citation

  • Muñoz Ortiz, Miguel & Kvalbein, Lisa & Hellemo, Lars, 2021. "Evaluation of open photovoltaic and wind production time series for Norwegian locations," Energy, Elsevier, vol. 236(C).
  • Handle: RePEc:eee:energy:v:236:y:2021:i:c:s0360544221016571
    DOI: 10.1016/j.energy.2021.121409
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221016571
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.121409?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. Eikeland, Odin Foldvik & Apostoleris, Harry & Santos, Sergio & Ingebrigtsen, Karoline & Boström, Tobias & Chiesa, Matteo, 2020. "Rethinking the role of solar energy under location specific constraints," Energy, Elsevier, vol. 211(C).
    2. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    3. Ryberg, David Severin & Caglayan, Dilara Gulcin & Schmitt, Sabrina & Linßen, Jochen & Stolten, Detlef & Robinius, Martin, 2019. "The future of European onshore wind energy potential: Detailed distribution and simulation of advanced turbine designs," Energy, Elsevier, vol. 182(C), pages 1222-1238.
    4. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    5. Moraes, L. & Bussar, C. & Stoecker, P. & Jacqué, Kevin & Chang, Mokhi & Sauer, D.U., 2018. "Comparison of long-term wind and photovoltaic power capacity factor datasets with open-license," Applied Energy, Elsevier, vol. 225(C), pages 209-220.
    6. 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.
    7. Henckes, Philipp & Frank, Christopher & Küchler, Nils & Peter, Jakob & Wagner, Johannes, 2020. "Uncertainty estimation of investment planning models under high shares of renewables using reanalysis data," Energy, Elsevier, vol. 208(C).
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Antonello Cammarano & Vincenzo Varriale & Francesca Michelino & Mauro Caputo, 2022. "Open and Crowd-Based Platforms: Impact on Organizational and Market Performance," Sustainability, MDPI, vol. 14(4), pages 1-26, February.
    2. Cheng, Xiong & Lv, Xin & Li, Xianshan & Zhong, Hao & Feng, Jia, 2023. "Market power evaluation in the electricity market based on the weighted maintenance object," Energy, Elsevier, vol. 284(C).
    3. Lujano-Rojas, Juan M. & Dufo-López, Rodolfo & Artal-Sevil, Jesús Sergio & García-Paricio, Eduardo, 2024. "Design of small-scale hybrid energy systems taking into account generation and demand uncertainties," Renewable Energy, Elsevier, vol. 227(C).
    4. Olkkonen, Ville & Lind, Arne & Rosenberg, Eva & Kvalbein, Lisa, 2023. "Electrification of the agricultural sector in Norway in an effort to phase out fossil fuel consumption," Energy, Elsevier, vol. 276(C).

    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. Kies, Alexander & Schyska, Bruno U. & Bilousova, Mariia & El Sayed, Omar & Jurasz, Jakub & Stoecker, Horst, 2021. "Critical review of renewable generation datasets and their implications for European power system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    2. Seljom, Pernille & Kvalbein, Lisa & Hellemo, Lars & Kaut, Michal & Ortiz, Miguel Muñoz, 2021. "Stochastic modelling of variable renewables in long-term energy models: Dataset, scenario generation & quality of results," Energy, Elsevier, vol. 236(C).
    3. 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).
    4. Shirizadeh, Behrang & Quirion, Philippe, 2022. "The importance of renewable gas in achieving carbon-neutrality: Insights from an energy system optimization model," Energy, Elsevier, vol. 255(C).
    5. 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).
    6. 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).
    7. Behrang Shirizadeh, 2020. "Carbon-neutral future with sector-coupling; relative role of different mitigation options in energy sector," Working Papers 2020.19, FAERE - French Association of Environmental and Resource Economists.
    8. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    9. Gruber, Katharina & Regner, Peter & Wehrle, Sebastian & Zeyringer, Marianne & Schmidt, Johannes, 2022. "Towards global validation of wind power simulations: A multi-country assessment of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the global wind atlas," Energy, Elsevier, vol. 238(PA).
    10. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    11. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    12. Lledó, Llorenç & Ramon, Jaume & Soret, Albert & Doblas-Reyes, Francisco-Javier, 2022. "Seasonal prediction of renewable energy generation in Europe based on four teleconnection indices," Renewable Energy, Elsevier, vol. 186(C), pages 420-430.
    13. Langer, Jannis & Zaaijer, Michiel & Quist, Jaco & Blok, Kornelis, 2023. "Introducing site selection flexibility to technical and economic onshore wind potential assessments: New method with application to Indonesia," Renewable Energy, Elsevier, vol. 202(C), pages 320-335.
    14. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    15. 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.
    16. 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.
    17. 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).
    18. Liu, Hailiang & Andresen, Gorm Bruun & Greiner, Martin, 2018. "Cost-optimal design of a simplified highly renewable Chinese electricity network," Energy, Elsevier, vol. 147(C), pages 534-546.
    19. Géremi Gilson Dranka & Paula Ferreira, 2020. "Electric Vehicles and Biofuels Synergies in the Brazilian Energy System," Energies, MDPI, vol. 13(17), pages 1-22, August.
    20. Gorre, Jachin & Ortloff, Felix & van Leeuwen, Charlotte, 2019. "Production costs for synthetic methane in 2030 and 2050 of an optimized Power-to-Gas plant with intermediate hydrogen storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    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:236:y:2021:i:c:s0360544221016571. 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.