Li, Zhijian, Hu, Yihua, Ollerenshaw, Richard et al. (3 more authors) (2025) Optimizing PV-battery energy storage for netzero emission traction power system through artificial rabbit optimization method. Journal of Energy Storage. 117069. ISSN 2352-1538
Abstract
The transition from traditional fossil fuels to renewable energy is becoming increasingly feasible and is essential for addressing energy and environmental challenges. In transportation electrification, the variability of power demand and the intermittent nature of renewable energy generation present challenges to achieving high renewable energy utilization. Battery energy storage systems (BESS) integrated to renewable resources offer a viable solution to these intermittency issues, though their costs require careful optimization. This paper explores the cost implications of using on-site renewable energy to power a railway traction system. It proposes a photovoltaic (PV) energy storage strategy optimized with the Artificial Rabbit Algorithm (ARO). By applying railway load and regional PV data, we optimize the capacity of BESS and the rated power of the PV site to meet railway electricity demands while minimizing investment and operational costs. The study shows that the capacity of BESS and the size of the PV installation depend on different self-sufficiency ratio (SSR) requirements, leading to an optimized configuration for highly renewable systems. Additionally, the study highlights that considering battery aging is crucial for reducing costs in traction power systems using renewable energy and remains economically viable under time-of-use pricing policies.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 Elsevier Ltd. This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy. |
Keywords: | Artificial rabbit optimization (ARO),Battery energy storage system (BESS),Optimal configuration,Photovoltaic (PV) |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 29 May 2025 09:10 |
Last Modified: | 29 May 2025 09:10 |
Published Version: | https://doi.org/10.1016/j.est.2025.117069 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1016/j.est.2025.117069 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:227211 |
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Description: Optimizing PV-Battery Energy Storage for NetZero Emission Traction Power System Through Artificial Rabbit Optimization Method_Revised
Licence: CC-BY 2.5