Bi-level Optimization of Sizing and Control Strategy of Hybrid Energy Storage System in Urban Rail Transit Considering Substation Operation Stability

Hongzhi Dong, Zhongbei Tian, Joseph Spencer, David Fletcher, Siavash Hajiabady

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Abstract

The hybrid energy storage system (HESS) which consists of battery and ultracapacitor can efficiently reduce the substation energy cost from grid and achieve the peak shaving function, due to its characteristics of high-power density and high-energy density. The sizing of HESS affects the operation cost of whole system. Besides, operation stability (like substation peak power and voltage fluctuations) is rarely considered in urban rail transit (URT) when sizing optimization of HESS is considered. Thus, this research proposes a sizing and control strategy optimization of HESS in URT. First, the mathematic model of URT with HESS is established, which is used to simulate URT and HESS operation state by power flow analysis method. Then, based on the proposed HESS control principle, a bi-level optimization of HESS in URT is proposed. The master level aims to optimize the rated capacity and power of HESS, reducing total operational cost. Then, the HESS control strategy is optimized at slave level, reducing substation peak power and voltage fluctuations of URT. The case study is conducted based on the data of Merseyrail line in Liverpool. A comparison is also conducted, which shows that the proposed method can reduce daily operation cost by 12.68% of the substation, while the grid energy cost is decreased by 57.26%.
Original languageEnglish
Article number10494394
Number of pages13
JournalIEEE Transactions on Transportation Electrification
Early online date8 Apr 2024
DOIs
Publication statusE-pub ahead of print - 8 Apr 2024

Bibliographical note

Funding:
This research is supported by the EPSRC (Connected and Coordinated Train Operation and Traction Power Supply Systems (COOPS), grant reference EP/Y003136/1).

Keywords

  • Urban railway transit
  • hybrid energy storage system
  • bi-level optimization

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