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Modelling and sizing of NaS (sodium sulfur) battery energy storage system for extending wind power performance in Crete Island

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  • Rodrigues, E.M.G.
  • Osório, G.J.
  • Godina, R.
  • Bizuayehu, A.W.
  • Lujano-Rojas, J.M.
  • Matias, J.C.O.
  • Catalão, J.P.S.

Abstract

Crete Island is rich in renewable energy resources such as wind and solar. Likewise other European territories, renewable sources already are being explored for power production. Currently a large amount of wind energy on Crete is curtailed during certain daily periods as a result of reduced demand and minimum operating levels on thermal generators. Reducing wind power curtailment magnitude requires additional sources of flexibility in the grid, and electric energy storage is one of them. This paper address wind generation curtailment minimization through the storage of wind energy surplus. NaS (sodium sulfura) battery modelling is used in this study in order to shift wind generation from off-peak to on-peak through a technical-economic analysis, considering the total annualized cost of the storage system and the wind power curtailment based on an annual basis. The obtained results are based on real data, which includes Crete Island demand, renewable and conventional power generation.

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  • Rodrigues, E.M.G. & Osório, G.J. & Godina, R. & Bizuayehu, A.W. & Lujano-Rojas, J.M. & Matias, J.C.O. & Catalão, J.P.S., 2015. "Modelling and sizing of NaS (sodium sulfur) battery energy storage system for extending wind power performance in Crete Island," Energy, Elsevier, vol. 90(P2), pages 1606-1617.
    • Handle: RePEc:eee:energy:v:90:y:2015:i:p2:p:1606-1617
    DOI: 10.1016/j.energy.2015.06.116
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    15. Jung, Chi-Young & Kim, Tae-Hyun & Kim, Wha-Jung & Yi, Sung-Chul, 2016. "Computational analysis of the zinc utilization in the primary zinc-air batteries," Energy, Elsevier, vol. 102(C), pages 694-704.
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    17. Vatanpour, Mohsen & Sadeghi Yazdankhah, Ahmad, 2018. "The impact of energy storage modeling in coordination with wind farm and thermal units on security and reliability in a stochastic unit commitment," Energy, Elsevier, vol. 162(C), pages 476-490.
    18. Ahmadian, Ali & Sedghi, Mahdi & Aliakbar-Golkar, Masoud & Elkamel, Ali & Fowler, Michael, 2016. "Optimal probabilistic based storage planning in tap-changer equipped distribution network including PEVs, capacitor banks and WDGs: A case study for Iran," Energy, Elsevier, vol. 112(C), pages 984-997.
    19. Stefano Bracco, 2020. "A Study for the Optimal Exploitation of Solar, Wind and Hydro Resources and Electrical Storage Systems in the Bormida Valley in the North of Italy," Energies, MDPI, vol. 13(20), pages 1-26, October.
    20. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
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