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

Jingjing Ye, Minghao Sun and Kejian Song ()
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Jingjing Ye: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Minghao Sun: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Kejian Song: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China

Energies, 2024, vol. 17, issue 1, 1-15

Abstract: 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.

Keywords: hybrid energy storage system; electric railway smart microgrid system; integrated empirical mode decomposition; two-stage energy distribution (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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