基于综合经验模式分解的电气化铁路智能微电网系统能源管理策略

IF 3 4区工程技术 Q3 ENERGY & FUELS Energies Pub Date : 2024-01-04 DOI:10.3390/en17010268

Jingjing Ye, Minghao Sun, Kejian Song

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引用次数: 0

摘要

将可再生能源和混合储能系统（HESS）集成到电气化铁路中，以建立电气化铁路智能微电网系统（ERSMS），有利于减少化石燃料消耗和能源浪费。然而，可再生能源发电量和牵引负荷的波动对这样一个复杂系统的能源管理有效性提出了挑战。本研究提出了一种能源管理策略，首先通过综合经验模式分解（IEMD）将可再生能源分解为低频和高频成分。然后，利用两阶段能量分配法对 ERSMS 中的能量流进行合理分配。最后，通过案例研究验证了所提解决方案的可行性和有效性。

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An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

The integration of a renewable energy and hybrid energy storage system (HESS) into electrified railways to build an electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the effectiveness of the energy management for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow in the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

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来源期刊

Energies ENERGY & FUELS-

CiteScore

6.20

自引率

21.90%

发文量

8045

审稿时长

1.9 months

期刊介绍： Energies (ISSN 1996-1073) is an open access journal of related scientific research, technology development and policy and management studies. It publishes reviews, regular research papers, and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.