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Control of battery storage for wind energy systems

机译:控制风能系统的电池存储

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This paper presents an optimization-based control strategy for the power management of a wind farm with battery storage. The strategy seeks to minimize the error between the power delivered by the wind farm with battery storage and the power demand from an operator. In addition, the strategy attempts to maximize battery life. The control strategy has two main stages. The first stage produces a family of control solutions that minimize the power error subject to the battery constraints over an optimization horizon. These solutions are parameterized by a given value for the state of charge at the end of the optimization horizon. The second stage screens the family of control solutions to select one attaining an optimal balance between power error and battery life. The battery life model used in this stage is a weighted Amp-hour (Ah) throughput model. The control strategy is modular, allowing for more sophisticated optimization models in the first stage, or more elaborate battery life models in the second stage. The strategy is implemented in real-time in the framework of Model Predictive Control (MPC).
机译:本文提出了一种基于优化的控制策略,用于带有电池存储的风电场的电源管理。该策略力求最大程度地减少风电场通过电池存储提供的电力与操作员的电力需求之间的误差。另外,该策略试图最大限度地延长电池寿命。控制策略有两个主要阶段。第一阶段产生一系列控制解决方案,这些控制解决方案可在优化范围内最大程度地减少受电池限制的功率误差。这些解决方案在优化范围结束时通过给定的充电状态值进行参数化。第二阶段筛选控制解决方案系列,以选择在功率误差和电池寿命之间达到最佳平衡的解决方案。此阶段中使用的电池寿命模型是加权安培小时(Ah)吞吐量模型。控制策略是模块化的,允许在第一阶段使用更复杂的优化模型,或者在第二阶段使用更复杂的电池寿命模型。该策略在模型预测控制(MPC)框架中实时实施。

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