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

• Published in: Energies (Basel) Vol. 17; no. 1; p. 268
• Main Authors: Ye, Jingjing, Sun, Minghao, Song, Kejian
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-01-2024
• Subjects: Alternative energy sources; Case studies; Efficiency; electric railway smart microgrid system; Energy consumption; Energy industry; Energy management; Energy management systems; Energy resources; Energy storage; Fourier transforms; hybrid energy storage system; integrated empirical mode decomposition; Methods; Power supply; Railroads; Renewable resources; Sediment transport; two-stage energy distribution; Wavelet transforms; Wind power
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en17010268

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.