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Journal of cleaner production, 2021-11, Vol.325, p.129247, Article 129247
2021

Details

Autor(en) / Beteiligte
Titel
Storage size determination for grid-connected wind power system based on power spectral density analysis
Ist Teil von
  • Journal of cleaner production, 2021-11, Vol.325, p.129247, Article 129247
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Elsevier ScienceDirect Journals Complete
Beschreibungen/Notizen
  • Energy storage system (ESS) is essential for wind power integration, and it has become more and more important to optimize the wind-energy storage system (WESS) for keeping power grid safe and stable. In this paper, a novel energy storage sizing approach which can improve the performance of WESS is put forward. Firstly, the hinges model is introduced into the power spectral density (PSD) analysis to obtain the low-pass decomposition frequency (LPDF), which is then used for energy storage sizing optimization based on the single-day energy balance. Secondly, a comprehensive evaluation criteria system based on cloud model is proposed to assess various characteristics of WESS. Thirdly, a case study based on a 30 MW wind farm indicates that the power curve of the proposed method meets the conditions for wind power integration, and the size and stability of ESS are optimized. Compared with the traditional filtering algorithms, the WESS performance of the proposed algorithm is improved by 77.55% than wavelet packet decomposition (WPD) and 65.84% than empirical mode decomposition (EMD), and its applicability in different time spans is also verified. •An approach to determine energy storage size is proposed by improved power spectral density analysis.•An evaluation system based on cloud model is designed to assess wind-energy storage system.•The system performance is improved by at least 65.84% through this method.•The effectiveness and applicability in different time spans are proved by case study.
Sprache
Englisch
Identifikatoren
ISSN: 0959-6526
eISSN: 1879-1786
DOI: 10.1016/j.jclepro.2021.129247
Titel-ID: cdi_crossref_primary_10_1016_j_jclepro_2021_129247

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