Model predictive control and improved low-pass filtering strategies based on wind power fluctuation mitigation

• DOI: 10.1007/s40565-018-0474-5
• Publication Date: 2018-12-26T11:16:17Z
• Authors: Yushu Sun; Xisheng Tang; Xiaozhe Sun; Dongqiang Jia; Zhihuang Cao; Jing Pan; Bin Xu
• Keywords: Smoothing; Model Predictive Control

The rapid development of renewable energy sources such as wind power has brought great challenges to the grid. Wind penetration can be improved by using hybrid storage (ES) mitigate fluctuation. We studied strategy smoothing fluctuation and ES distribution. Firstly, an effective control extracted comparing constant-time low-pass filtering (CLF), variable-time (VLF), wavelet packet decomposition (WPD), empirical mode (EMD) model predictive algorithms with rate constraints identical grid-connected power. Moreover, mean frequency cut-off acquired Hilbert Huang transform (HHT), time constant algorithm obtained. Then, (ILFA) is proposed achieve allocation between lithium battery (LB) supercapacitor (SC), which overcome over-charge over-discharge in traditional (TLFA). In addition, optimized LB SC are further obtained based on priority combined fuzzy (FC) method. Finally, simulation results show that effectively suppressed strategies, beneficial system.