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A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns

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  • Cradden, Lucy C.
  • McDermott, Frank
  • Zubiate, Laura
  • Sweeney, Conor
  • O'Malley, Mark

Abstract

To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern.

Suggested Citation

  • Cradden, Lucy C. & McDermott, Frank & Zubiate, Laura & Sweeney, Conor & O'Malley, Mark, 2017. "A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns," Renewable Energy, Elsevier, vol. 106(C), pages 165-176.
    • Handle: RePEc:eee:renene:v:106:y:2017:i:c:p:165-176
    DOI: 10.1016/j.renene.2016.12.079
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    References listed on IDEAS

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    2. Lynch, Muireann Á & Devine, Mel & Bertsch, Valentin, 2018. "The role of power-to-gas in the future energy system: how much is needed and who wants to invest?," Papers WP590, Economic and Social Research Institute (ESRI).
    3. Mel T. Devine & Valentin Bertsch, 2023. "The role of demand response in mitigating market power: a quantitative analysis using a stochastic market equilibrium model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 555-597, June.
    4. 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).
    5. Heinen, Steve & Turner, William & Cradden, Lucy & McDermott, Frank & O'Malley, Mark, 2017. "Electrification of residential space heating considering coincidental weather events and building thermal inertia: A system-wide planning analysis," Energy, Elsevier, vol. 127(C), pages 136-154.
    6. Coker, Phil J. & Bloomfield, Hannah C. & Drew, Daniel R. & Brayshaw, David J., 2020. "Interannual weather variability and the challenges for Great Britain’s electricity market design," Renewable Energy, Elsevier, vol. 150(C), pages 509-522.
    7. Newbery, David, 2021. "National Energy and Climate Plans for the island of Ireland: wind curtailment, interconnectors and storage," Energy Policy, Elsevier, vol. 158(C).
    8. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    9. Bertsch, Valentin & Devine, Mel & Sweeney, Conor & Parnell, Andrew C., 2018. "Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model," Papers WP585, Economic and Social Research Institute (ESRI).
    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. Bertsch, Valentin & Devine, Mel, 2019. "The Role of Demand Response in Mitigating Market Power — A Quantitative Analysis Using a Stochastic Market Equilibrium Model," Papers WP635, Economic and Social Research Institute (ESRI).
    12. Commin, Andrew N. & French, Andrew S. & Marasco, Matteo & Loxton, Jennifer & Gibb, Stuart W. & McClatchey, John, 2017. "The influence of the North Atlantic Oscillation on diverse renewable generation in Scotland," Applied Energy, Elsevier, vol. 205(C), pages 855-867.
    13. Lynch, Muireann & Devine, Mel T. & Bertsch, Valentin, 2019. "The role of power-to-gas in the future energy system: Market and portfolio effects," Energy, Elsevier, vol. 185(C), pages 1197-1209.

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