尺寸
风力发电
储能
希尔伯特-黄变换
功率(物理)
电力系统
网格
能量(信号处理)
计算机科学
控制理论(社会学)
工程类
电气工程
滤波器(信号处理)
数学
几何学
控制(管理)
人工智能
视觉艺术
艺术
物理
统计
量子力学
作者
Lujin Yao,Wei Wang,Wei Cai,Jizhen Liu
标识
DOI:10.1016/j.jclepro.2021.129247
摘要
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.
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