使用高级模型释放电网电池的额外价值
Unlocking Extra Value from Grid Batteries Using Advanced Models
摘要：
锂离子电池越来越多地被部署在自由化的电力系统中，在特定的市场环境下，它们的使用是由经济优化驱动的。然而，电池退化强烈地取决于操作简档，并且这在能量交易应用中特别可变。在这里，我们介绍了一个为期一年的实验结果，其中对电池进行了循环，通过解决批发能源交易的经济优化问题计算出配置文件，包括物理驱动的退化模型作为约束。结果证实了先前模拟的结论，并表明与现有方法相比，这种方法可以增加20%的收入，同时减少30%的退化。对数据的分析表明，传统方法无法增加电池在其寿命期间可以管理的循环次数，但基于物理的方法在年数和循环次数以及每年的收入方面都增加了寿命，将可能的寿命收入增加了70%。最后，结果表明模型不准确的经济影响，表明基于物理的模型可以将整体业务案例的差异从170%减少到13%。有可能使用控制工程结合电池老化的物理模型来解锁显着的额外性能。
英文摘要：
Lithium-ion batteries are increasingly being deployed in liberalised electricity systems, where their use is driven by economic optimisation in a specific market context. However, battery degradation depends strongly on operational profile, and this is particularly variable in energy trading applications. Here, we present results from a year-long experiment where pairs of batteries were cycled with profiles calculated by solving an economic optimisation problem for wholesale energy trading, including a physically-motivated degradation model as a constraint. The results confirm the conclusions of previous simulations and show that this approach can increase revenue by 20% whilst simultaneously decreasing degradation by 30% compared to existing methods. Analysis of the data shows that conventional approaches cannot increase the number of cycles a battery can manage over its lifetime, but the physics-based approach increases the lifetime both in terms of years and number of cycles, as well as the revenue per year, increasing the possible lifetime revenue by 70%. Finally, the results demonstrate the economic impact of model inaccuracies, showing that the physics-based model can reduce the discrepancy in the overall business case from 170% to 13%. There is potential to unlock significant extra performance using control engineering incorporating physical models of battery ageing.
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