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Optimal Operation of Grid-Tied Energy Storage Systems Considering Detailed Device-Level Battery Models

机译:考虑详细的设备级电池型号的网格绑定能量存储系统的最佳运行

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摘要

The current optimization-based algorithms to operate grid-tied battery energy storage systems (BESS) typically do not look much under the hood of the BESS, i.e., the device-level characteristics of the batteries. This is often due to modeling as well as optimization complexities. However, simplified models may significantly degrade the performance of BESS operation in practice. Therefore, in this article, we propose a new BESS scheduling optimization framework that accounts for features such as cell-to-cell variations in maximum capacity, charge level balance, and internal resistance. The proposed framework is in the form of tractable mixed integer linear programs. Our approach is to estimate and update the device-level battery model parameters continuously, without the need to interrupt BESS normal operation. We validate the performance compared to an offline approach, which is based on dedicated model testing and calibration. To assure accurate performance evaluation, this article also includes developing a power hardware-in-the-loop testbed that allows for flexible operation and detailed monitoring of BESS under different design scenarios.
机译:基于当前的优化基于电池捆绑电池储能系统(BESS)的算法通常在贝塞的罩下看起来不太在电池的设备级特征下。这通常是由于建模以及优化复杂性。然而,简化的模型可能会在实践中显着降低贝塞操作的性能。因此,在本文中,我们提出了一种新的BESS调度优化框架,其考虑了最大容量,充电水平平衡和内阻等特征的特征。所提出的框架是易于混合整数线性程序的形式。我们的方法是连续估计和更新设备级电池模型参数,无需中断BESS正常操作。与离线方法相比,我们验证了性能,这是基于专用模型测试和校准。为了确保准确的绩效评估,本文还包括开发电源硬件in-in-Loop测试设备,允许在不同的设计方案下灵活的操作和详细监控BESS。

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