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A simplified model for estimating the monthly performance of autonomous wind energy systems with battery storage

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  • Celik, A.N.

Abstract

This paper presents a simplified algorithm to estimate the monthly performance of autonomous small-scale wind energy systems with battery storage. The novel model is drawn based on the simulation results, using eight-year long hour-by-hour measured wind speed data from five different locations throughout the world. An hourly constant load profile is used. The renewable energy simulation program (ARES) of the Cardiff School of Engineering is used. The ARES simulates the battery state of voltage (SoV) and is able to predict the system performance.

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  • Celik, A.N., 2003. "A simplified model for estimating the monthly performance of autonomous wind energy systems with battery storage," Renewable Energy, Elsevier, vol. 28(4), pages 561-572.
    • Handle: RePEc:eee:renene:v:28:y:2003:i:4:p:561-572
    DOI: 10.1016/S0960-1481(02)00067-8
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    5. Lujano-Rojas, Juan M. & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2012. "Optimal sizing of small wind/battery systems considering the DC bus voltage stability effect on energy capture, wind speed variability, and load uncertainty," Applied Energy, Elsevier, vol. 93(C), pages 404-412.
    6. Dalton, G.J. & Lockington, D.A. & Baldock, T.E., 2008. "Feasibility analysis of stand-alone renewable energy supply options for a large hotel," Renewable Energy, Elsevier, vol. 33(7), pages 1475-1490.
    7. Deshmukh, M.K. & Deshmukh, S.S., 2008. "Modeling of hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 235-249, January.
    8. Gupta, R.A. & Kumar, Rajesh & Bansal, Ajay Kumar, 2015. "BBO-based small autonomous hybrid power system optimization incorporating wind speed and solar radiation forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1366-1375.
    9. Masmoudi, Abdelkarim & Abdelkafi, Achraf & Krichen, Lotfi, 2011. "Electric power generation based on variable speed wind turbine under load disturbance," Energy, Elsevier, vol. 36(8), pages 5016-5026.
    10. Zamani-Dehkordi, Payam & Shafiee, Soroush & Rakai, Logan & Knight, Andrew M. & Zareipour, Hamidreza, 2017. "Price impact assessment for large-scale merchant energy storage facilities," Energy, Elsevier, vol. 125(C), pages 27-43.
    11. Sawle, Yashwant & Gupta, S.C. & Bohre, Aashish Kumar, 2018. "Review of hybrid renewable energy systems with comparative analysis of off-grid hybrid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2217-2235.
    12. Masseran, Nurulkamal, 2015. "Evaluating wind power density models and their statistical properties," Energy, Elsevier, vol. 84(C), pages 533-541.
    13. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    14. Asma Mohamad Aris & Bahman Shabani, 2015. "Sustainable Power Supply Solutions for Off-Grid Base Stations," Energies, MDPI, vol. 8(10), pages 1-38, September.
    15. Lund, Henrik, 2005. "Large-scale integration of wind power into different energy systems," Energy, Elsevier, vol. 30(13), pages 2402-2412.
    16. Lund, H & Münster, E, 2003. "Modelling of energy systems with a high percentage of CHP and wind power," Renewable Energy, Elsevier, vol. 28(14), pages 2179-2193.
    17. 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.

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