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Application of online empirical mode decomposition and continuous wavelet transform for Power Smoothing in Low-voltage Microgrid with Battery Energy Storage System

机译:在线经验模式分解和连续小波变换在低压微电池电气平滑电池储能系统中的应用

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With the advent of microgrids (MG) and increasing use of renewable energy sources (RES), conventional low voltage networks change their structure from passive to active. The inherent oscillation nature of RESs, such as wind turbine units (WT), can lead to adverse effects such as power quality and system stability issues. therefore, the use of energy storage systems (ESSs) becomes one feasible solution to mitigate the output power fluctuations of the WT unit. In this paper, a Battery Energy Storage System (BESS) is used in order to smooth the power fluctuations based on a two-level control strategy include active power smoothing and reactive power compensation and also power management system. Various signal processing methods are applied to power smoothing level, and among all of them, the continuous wavelet transform (CWT) demonstrated the best performance. The effectiveness of the control strategy is verified using MATLAB/Simulink software.
机译:随着微电网(MG)的出现并越来越多使用可再生能源(RES),传统的低压网络将其结构从被动变为有效。 RES的固有振荡性质,如风力涡轮机单元(WT),可以导致电力质量和系统稳定性问题等不利影响。 因此,使用能量存储系统(ESS)成为一种可行的解决方案,以减轻WT单元的输出功率波动。 在本文中,使用电池储能系统(BESS)以平滑基于双层控制策略的功率波动包括有源功率平滑和无功功率补偿以及电源管理系统。 各种信号处理方法适用于功率平滑水平,并且在所有信号中,连续小波变换(CWT)展示了最佳性能。 使用Matlab / Simulink软件验证控制策略的有效性。

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