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A Method for Estimating Annual Energy Production Using Monte Carlo Wind Speed Simulation

Author

Listed:
  • Birgir Hrafnkelsson

    (Faculty of Physical Sciences, Department of Mathematics, University of Iceland, Reykjavik IS-107, Iceland)

  • Gudmundur V. Oddsson

    (Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, Centre for Productivity, Performance and Processes, University of Iceland, Hjardarhagi 6,107, Reykjavik IS-107, Iceland)

  • Runar Unnthorsson

    (Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, Centre for Productivity, Performance and Processes, University of Iceland, Hjardarhagi 6,107, Reykjavik IS-107, Iceland)

Abstract

A novel Monte Carlo (MC) approach is proposed for the simulation of wind speed samples to assess the wind energy production potential of a site. The Monte Carlo approach is based on historical wind speed data and reserves the effect of autocorrelation and seasonality in wind speed observations. No distributional assumptions are made, and this approach is relatively simple in comparison to simulation methods that aim at including the autocorrelation and seasonal effects. Annual energy production (AEP) is simulated by transforming the simulated wind speed values via the power curve of the wind turbine at the site. The proposed Monte Carlo approach is generic and is applicable for all sites provided that a sufficient amount of wind speed data and information on the power curve are available. The simulated AEP values based on the Monte Carlo approach are compared to both actual AEP and to simulated AEP values based on a modified Weibull approach for wind speed simulation using data from the Burfell site in Iceland. The comparison reveals that the simulated AEP values based on the proposed Monte Carlo approach have a distribution that is in close agreement with actual AEP from two test wind turbines at the Burfell site, while the simulated AEP of the Weibull approach is such that the P50 and the scale are substantially lower and the P90 is higher. Thus, the Weibull approach yields AEP that is not in line with the actual variability in AEP, while the Monte Carlo approach gives a realistic estimate of the distribution of AEP.

Suggested Citation

  • Birgir Hrafnkelsson & Gudmundur V. Oddsson & Runar Unnthorsson, 2016. "A Method for Estimating Annual Energy Production Using Monte Carlo Wind Speed Simulation," Energies, MDPI, vol. 9(4), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:4:p:286-:d:68146
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    References listed on IDEAS

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    Cited by:

    1. Ali Marjan & Mahmood Shafiee, 2018. "Evaluation of Wind Resources and the Effect of Market Price Components on Wind-Farm Income: A Case Study of Ørland in Norway," Energies, MDPI, vol. 11(11), pages 1-21, October.
    2. María del Carmen Gómez-Ríos & David Juárez-Luna, 2019. "Costo de generación eléctrica incorporando externalidades ambientales: Mezcla óptima de tecnologías de carga base," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(3), pages 353-377, Julio - S.
    3. 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).
    4. Maria del Carmen Gomez-Rios & Dora Carmen Galvez-Cruz, 2021. "Simulation of Levelized Costs of Electricity Considering Externalities," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-23, Octubre -.
    5. Yun, Eunjeong & Hur, Jin, 2021. "Probabilistic estimation model of power curve to enhance power output forecasting of wind generating resources," Energy, Elsevier, vol. 223(C).
    6. Ayik, A. & Ijumba, N. & Kabiri, C. & Goffin, P., 2021. "Preliminary wind resource assessment in South Sudan using reanalysis data and statistical methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    7. Gómez-Ríos, María del Carmen & Juárez-Luna, David, 2018. "Precio de las emisiones de CO2 en la generación eléctrica [Price of CO2 emissions in electricity generation]," MPRA Paper 89915, University Library of Munich, Germany.

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