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12 October 2022
Risk-based Two-stage Optimal Scheduling of Energy Storage System with Second-life Battery Units
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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.
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Risk-based Two-stage Optimal Scheduling of Energy Storage System with Second-life Battery Units
(
),
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.
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