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A simplified model for estimating yearly wind fraction in hybrid-wind energy systems

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  • Celik, A.N.

Abstract

This article presents a simplified algorithm to estimate the yearly wind fraction, the fraction of energy demand provided by wind generator, in a hybrid-wind system (typically a PV-wind) with battery storage. The novel model is drawn based on the simulation results, using 8-year long measured hour-by-hour wind speed data from five different locations throughout the world. The simulation program simulates the battery state of voltage (SoV) and is able to predict the wind fraction for a period of time, typically monthly or yearly. The yearly wind fraction values obtained from the simulations are plotted against the ratio of energy to load for various battery storage capacities to obtain wind fraction curves. The novel method correlates the yearly wind fraction with the parameters of the Weibull distribution function, thus, offering a general methodology. The yearly wind fraction curves are mathematically represented using a 2-parameter model. The novel algorithm is validated by comparing the simulated wind fraction values with those calculated from the simplified algorithm. The standard error of estimation of the WF from the simplified algorithm is further presented for each battery capacity.

Suggested Citation

  • Celik, A.N., 2006. "A simplified model for estimating yearly wind fraction in hybrid-wind energy systems," Renewable Energy, Elsevier, vol. 31(1), pages 105-118.
    • Handle: RePEc:eee:renene:v:31:y:2006:i:1:p:105-118
    DOI: 10.1016/j.renene.2005.03.006
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    5. Ouammi, Ahmed & Dagdougui, Hanane & Sacile, Roberto & Mimet, Abdelaziz, 2010. "Monthly and seasonal assessment of wind energy characteristics at four monitored locations in Liguria region (Italy)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1959-1968, September.
    6. Ouammi, Ahmed & Ghigliotti, Valeria & Robba, Michela & Mimet, Abdelaziz & Sacile, Roberto, 2012. "A decision support system for the optimal exploitation of wind energy on regional scale," Renewable Energy, Elsevier, vol. 37(1), pages 299-309.
    7. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    8. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.
    9. Elio Chiodo & Bassel Diban & Giovanni Mazzanti & Fabio De Angelis, 2023. "A Review on Wind Speed Extreme Values Modeling and Bayes Estimation for Wind Power Plant Design and Construction," Energies, MDPI, vol. 16(14), pages 1-20, July.

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