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Lifetime Cost Optimized Wind Power Control Using Hybrid Energy Storage System

机译:使用混合能量存储系统的寿命优化风电控制

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This paper presents the use of hybrid energy storage, composed of ultracapacitor and Lithium-ion battery, to improve wind power stability. A control algorithm based on artificial neural network is proposed to manage the run-time use of the hybrid energy storage system to (1) optimize wind power predictability hence power grid stability, and (2) minimize the overall lifetime cost of the energy storage system. Evaluations using wind farm data demonstrate that, compared with two recently proposed control methods, the proposed control algorithm can extend system lifetime by 62% and 143%, and reduce the overall lifetime energy storage system cost (20 years) by 41% and 59%, respectively.
机译:本文介绍了使用超容量和锂离子电池组成的混合储能,以提高风力稳定性。提出了一种基于人工神经网络的控制算法来管理混合能量存储系统的运行时间使用(1)优化风力电力可预测性,因此电网稳定性,(2)最小化能量存储系统的整体寿命成本。使用风电场数据的评估表明,与最近提出的两个控制方法相比,所提出的控制算法可以将系统寿命延长62%和143%,并将整体寿命能量储存系统成本(20年)降低41%和59% , 分别。

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