IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v189y2019ics0360544219319073.html
   My bibliography  Save this article

Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil

Author

Listed:
  • Gruber, Katharina
  • Klöckl, Claude
  • Regner, Peter
  • Baumgartner, Johann
  • Schmidt, Johannes

Abstract

NASA's MERRA-2 reanalysis is a widely used dataset in renewable energy resource modelling. The Global Wind Atlas (GWA) has been used to bias-correct MERRA-2 data before. There is, however, a lack of an analysis of the performance of MERRA-2 with bias correction from GWA on different spatial levels – and for regions outside of Europe, China or the United States. This study therefore evaluates different methods for wind power simulation on four spatial resolution levels from wind park to national level in Brazil. In particular, spatial interpolation methods and spatial as well as spatiotemporal wind speed bias correction using local wind speed measurements and mean wind speeds from the GWA are assessed. By validating the resulting timeseries against observed generation it is assessed at which spatial levels the different methods improve results – and whether global information derived from the GWA can compete with locally measured wind speed data as a source of bias correction. Results show that (i) bias correction with the GWA improves results on state, sub-system, and national-level, but not on wind park level, that (ii) the GWA improves results comparably to local measurements, and that (iii) complex spatial interpolation methods do not contribute in improving quality of the simulation.

Suggested Citation

  • Gruber, Katharina & Klöckl, Claude & Regner, Peter & Baumgartner, Johann & Schmidt, Johannes, 2019. "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319073
    DOI: 10.1016/j.energy.2019.116212
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219319073
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116212?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. Schmidt, Johannes & Cancella, Rafael & Junior, Amaro Olímpio Pereira, 2016. "The effect of windpower on long-term variability of combined hydro-wind resources: The case of Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 131-141.
    2. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    3. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    4. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Lara-Fanego, V. & Tovar-Pescador, J., 2014. "A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power," Renewable Energy, Elsevier, vol. 69(C), pages 147-156.
    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. 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).
    2. Johann Baumgartner & Katharina Gruber & Sofia G. Simoes & Yves-Marie Saint-Drenan & Johannes Schmidt, 2020. "Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja," Energies, MDPI, vol. 13(9), pages 1-23, May.
    3. 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.
    4. 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).
    5. 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).
    6. 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.
    7. Pflugfelder, Yannik & Kramer, Hendrik & Weber, Christoph, 2024. "A novel approach to generate bias-corrected regional wind infeed timeseries based on reanalysis data," Applied Energy, Elsevier, vol. 361(C).
    8. Castro, Gabriel Malta & Klöckl, Claude & Regner, Peter & Schmidt, Johannes & Pereira, Amaro Olimpio, 2022. "Improvements to Modern Portfolio Theory based models applied to electricity systems," Energy Economics, Elsevier, vol. 111(C).
    9. Hai Lin & Yi Yang & Shuguang Wang & Shuyu Wang & Jianping Tang & Guangtao Dong, 2023. "Evaluation of MSWX Bias-Corrected Meteorological Forcing Datasets in China," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    10. Santos, Fábio Sandro dos & Nascimento, Kerolly Kedma Felix do & Jale, Jader da Silva & Stosic, Tatijana & Marinho, Manoel H.N. & Ferreira, Tiago A.E., 2021. "Mixture distribution and multifractal analysis applied to wind speed in the Brazilian Northeast region," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    11. Luzia, Graziela & Koivisto, Matti J. & Hahmann, Andrea N., 2023. "Validating EURO-CORDEX climate simulations for modelling European wind power generation," Renewable Energy, Elsevier, vol. 217(C).
    12. Murcia, Juan Pablo & Koivisto, Matti Juhani & Luzia, Graziela & Olsen, Bjarke T. & Hahmann, Andrea N. & Sørensen, Poul Ejnar & Als, Magnus, 2022. "Validation of European-scale simulated wind speed and wind generation time series," Applied Energy, Elsevier, vol. 305(C).
    13. Prasad, Abhnil Amtesh & Yang, Yuqing & Kay, Merlinde & Menictas, Chris & Bremner, Stephen, 2021. "Synergy of solar photovoltaics-wind-battery systems in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    14. Katikas, Loukas & Dimitriadis, Panayiotis & Koutsoyiannis, Demetris & Kontos, Themistoklis & Kyriakidis, Phaedon, 2021. "A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series," Applied Energy, Elsevier, vol. 295(C).
    15. 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).
    16. José Rafael Dorrego Portela & Geovanni Hernández Galvez & Quetzalcoatl Hernandez-Escobedo & Ricardo Saldaña Flores & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & Pascual López de Paz & A, 2022. "Microscale Wind Assessment, Comparing Mesoscale Information and Observed Wind Data," Sustainability, MDPI, vol. 14(19), pages 1-12, September.
    17. Erika Carvalho Nogueira & Rafael Cancella Morais & Amaro Olimpio Pereira, 2023. "Offshore Wind Power Potential in Brazil: Complementarity and Synergies," Energies, MDPI, vol. 16(16), pages 1-18, August.
    18. Gabriel Malta Castro & Claude Klockl & Peter Regner & Johannes Schmidt & Amaro Olimpio Pereira Jr, 2021. "Improvements to Modern Portfolio Theory based models applied to electricity systems," Papers 2105.08182, arXiv.org.
    19. Nouri, Milad & Homaee, Mehdi, 2022. "Reference crop evapotranspiration for data-sparse regions using reanalysis products," Agricultural Water Management, Elsevier, vol. 262(C).
    20. Geovanni Hernández Galvez & Daniel Chuck Liévano & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & José Rafael Dorrego Portela & Antonio Trujillo Narcía & Ricardo Saldaña Flores & Liliana P, 2022. "Harnessing Offshore Wind Energy along the Mexican Coastline in the Gulf of Mexico—An Exploratory Study including Sustainability Criteria," Sustainability, MDPI, vol. 14(10), pages 1-26, May.

    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. 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).
    2. Zappa, William & van den Broek, Machteld, 2018. "Analysing the potential of integrating wind and solar power in Europe using spatial optimisation under various scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1192-1216.
    3. Ingeborg Graabak & Magnus Korpås, 2016. "Variability Characteristics of European Wind and Solar Power Resources—A Review," Energies, MDPI, vol. 9(6), pages 1-31, June.
    4. Christina Carty & Oscar Claveria, 2022. "“The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis”," AQR Working Papers 202205, University of Barcelona, Regional Quantitative Analysis Group, revised May 2022.
    5. Liang, Yushi & Wu, Chunbing & Ji, Xiaodong & Zhang, Mulan & Li, Yiran & He, Jianjun & Qin, Zhiheng, 2022. "Estimation of the influences of spatiotemporal variations in air density on wind energy assessment in China based on deep neural network," Energy, Elsevier, vol. 239(PC).
    6. Dunguo Mou, 2018. "Wind Power Development and Energy Storage under China’s Electricity Market Reform—A Case Study of Fujian Province," Sustainability, MDPI, vol. 10(2), pages 1-20, January.
    7. Brunner, Christoph & Deac, Gerda & Braun, Sebastian & Zöphel, Christoph, 2020. "The future need for flexibility and the impact of fluctuating renewable power generation," Renewable Energy, Elsevier, vol. 149(C), pages 1314-1324.
    8. Arjuna Nebel & Christine Krüger & Tomke Janßen & Mathieu Saurat & Sebastian Kiefer & Karin Arnold, 2020. "Comparison of the Effects of Industrial Demand Side Management and Other Flexibilities on the Performance of the Energy System," Energies, MDPI, vol. 13(17), pages 1-20, August.
    9. Min, C.G. & Park, J.K. & Hur, D. & Kim, M.K., 2016. "A risk evaluation method for ramping capability shortage in power systems," Energy, Elsevier, vol. 113(C), pages 1316-1324.
    10. Tania García-Sánchez & Arbinda Kumar Mishra & Elías Hurtado-Pérez & Rubén Puché-Panadero & Ana Fernández-Guillamón, 2020. "A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine," Energies, MDPI, vol. 13(21), pages 1-16, November.
    11. Ben Christopher, S.J. & Carolin Mabel, M., 2020. "A bio-inspired approach for probabilistic energy management of micro-grid incorporating uncertainty in statistical cost estimation," Energy, Elsevier, vol. 203(C).
    12. Cheng-Dar Yue & Yi-Shegn Chiu & Chien-Cheng Tu & Ta-Hui Lin, 2020. "Evaluation of an Offshore Wind Farm by Using Data from the Weather Station, Floating LiDAR, Mast, and MERRA," Energies, MDPI, vol. 13(1), pages 1-20, January.
    13. Andrychowicz, Mateusz & Olek, Blazej & Przybylski, Jakub, 2017. "Review of the methods for evaluation of renewable energy sources penetration and ramping used in the Scenario Outlook and Adequacy Forecast 2015. Case study for Poland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 703-714.
    14. Huang, Mengdi & Chang, Jianxia & Guo, Aijun & Zhao, Mingzhe & Ye, Xiangmin & Lei, Kaixuan & Peng, Zhiwen & Wang, Yimin, 2023. "Cascade hydropower stations optimal dispatch considering flexible margin in renewable energy power system," Energy, Elsevier, vol. 285(C).
    15. Mararakanye, Ndamulelo & Bekker, Bernard, 2019. "Renewable energy integration impacts within the context of generator type, penetration level and grid characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 441-451.
    16. Pacheco, A. & Gorbeña, E. & Sequeira, C. & Jerez, S., 2017. "An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal," Energy, Elsevier, vol. 131(C), pages 239-250.
    17. Daniel Ambach & Robert Garthoff, 2016. "Vorhersagen der Windgeschwindigkeit und Windenergie in Deutschland," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 15-36, February.
    18. Pape, Christian, 2018. "The impact of intraday markets on the market value of flexibility — Decomposing effects on profile and the imbalance costs," Energy Economics, Elsevier, vol. 76(C), pages 186-201.
    19. Sinn, Hans-Werner, 2017. "Buffering volatility: A study on the limits of Germany's energy revolution," European Economic Review, Elsevier, vol. 99(C), pages 130-150.
    20. Álvarez-García, Francisco J. & Fresno-Schmolk, Gonzalo & OrtizBevia, María J. & Cabos, William & RuizdeElvira, Antonio, 2020. "Reduction of aggregate wind power variability using Empirical Orthogonal Teleconnections: An application in the Iberian Peninsula," Renewable Energy, Elsevier, vol. 159(C), pages 151-161.

    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:189:y:2019:i:c:s0360544219319073. 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.