Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/169616
Title: Risk-based two-stage optimal scheduling of energy storage system with second-life battery units
Authors: Zhang, Yongxi
Zhu, Jiahua
Xu, Yan
Zhou, Renjun
Dong, Zhao Yang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2023
Source: Zhang, Y., Zhu, J., Xu, Y., Zhou, R. & Dong, Z. Y. (2023). Risk-based two-stage optimal scheduling of energy storage system with second-life battery units. CSEE Journal of Power and Energy Systems, 9(2), 529-538. https://dx.doi.org/10.17775/CSEEJPES.2021.06860
Journal: CSEE Journal of Power and Energy Systems 
Abstract: With the growing adoption of Electrical Vehicles (EVs), it is expected that a large number of on-board Li-ion batteries will be retired from EVs in the near future. Retired batteries will typically retain 80% of their initial capacities and can be recycled as second life batteries (SLBs). Although the capital costs of SLBs are much cheaper, their operational reliability is an important concern since used batteries may suffer from a higher failure rate. This paper aggregates brand new batteries and SLBs together to improve power system's operating performance with renewable energy resources. In the context of a day-ahead and intra-day dispatch framework, a two-stage coordinated optimal scheduling method is proposed. Specifically, the energy cost of brand-new batteries and SLBs is calculated based on detailed battery degradation model, and the reliability of batteries is modeled based on the Weibull distribution. Moreover, Conditional value at risk (CVaR) criterion is applied to evaluate the risk induced by intermittent renewable power output, load demand variation and SLBs failure probability. Simulation tests demonstrate the effectiveness of the proposed method.
URI: https://hdl.handle.net/10356/169616
ISSN: 2096-0042
DOI: 10.17775/CSEEJPES.2021.06860
Schools: School of Electrical and Electronic Engineering 
Rights: © 2021 CSEE. Published by IEEE. This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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