Sizeable lithium-ion battery (LIB) sources in the transportation and power sectors provide a promising approach to alleviate the increasing volatility in energy systems. To dispatch LIBs durably and safely, operators need to estimate the battery power characteristics, which are commonly derived from external states of the battery obtained by empirical models. However, the internal states that play a decisive role are rarely considered. In this work, the power characterization is based on an interpretable and analytical electrochemical model. In addition to external states, internal states, including Li-ion concentrations, side reaction rates, and the energy conversion efficiency, are considered in the characterization. Since the dispatch time interval is usually longer than the time resolution of the battery model, an optimization-based approach taking the idea of model predictive control is designed for efficient calculation. A linearization scheme is proposed to embed power characteristics into the optimization-based dispatch of an integrated energy-transportation system with low complexity. Case studies on LiNCM and LiFePO4_{4} batteries in different temperatures are conducted. The calculation of power characteristics takes about two minutes. By considering power characteristics, the energy conversion efficiency of the dispatched battery can be increased by 5%–15%. At the same time, the degradation stress and heat generation can be reduced to around one-fourth of the naïve case.

中文翻译：

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通过可行的功率表征增强集成能源传输系统中锂离子电池源的可调度性


交通和电力领域的大量锂离子电池（LIB）资源为缓解能源系统日益加剧的波动性提供了一种有前景的方法。为了持久、安全地调度锂离子电池，运营商需要估计电池功率特性，这些特性通常是根据经验模型获得的电池外部状态得出的。然而，起决定性作用的内部状态却很少被考虑。在这项工作中，功率表征基于可解释和分析的电化学模型。除了外部状态之外，在表征中还考虑了内部状态，包括锂离子浓度、副反应速率和能量转换效率。由于调度时间间隔通常比电池模型的时间分辨率长，因此采用模型预测控制的思想，设计了一种基于优化的方法来实现高效计算。提出了一种线性化方案，将功率特性嵌入到复杂度较低的综合能源运输系统的基于优化的调度中。对不同温度下的LiNCM和LiFePO4_{4}电池进行了案例研究。功率特性的计算大约需要两分钟。考虑功率特性，调度电池的能量转换效率可提高5%~15%。同时，降解应力和热量产生可以减少到原始情况的四分之一左右。