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ADALINE (ADAptive Linear NEuron)-based coordinated control for wind power fluctuations smoothing with reduced BESS (battery energy storage system) capacity

机译:基于ADALINE(自适应线性NEuron)的协调控制,用于通过减少BESS(电池储能系统)容量来平滑风电波动

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摘要

Most wind turbine generators installed in large wind farms are variable speed types which operate at the maximum power point tracking mode in order to increase the power generation. Due to this fact and regarding the random nature of the wind speed, the output power of the wind farm fluctuates randomly. Fluctuating power affects network operation and needs to be smoothed. In order to mitigate the output power fluctuations of a wind farm, a 4-step coordinated control technique based on ADALINE (ADAptive Linear NEuron) is proposed in this paper which uses a small BESS (Battery Energy Storage System) capacity. At first the on-line tracking of the WFOP (Wind Farm Output Power) is carried out by ADALINE. Afterwards, two constraints for maximum permissible fluctuations are imposed on the ADALINE output. Two states of charging feedback control strategies are implemented in the third and fourth steps. Reducing the battery capacity in proposed coordinated control technique is fulfilled through the accurate tracking performed by ADALINE and also by maintaining the level of BESS saved energy within the batteries safe performance region performed by state of charging feedback control strategies. Simulation results run by real data verify that the performance of the proposed approach is considerably better than the basic approach. (C) 2016 Elsevier Ltd. All rights reserved.
机译:安装在大型风电场中的大多数风力发电机都是变速类型的,它们以最大功率点跟踪模式运行,以增加发电量。由于这个事实,并且考虑到风速的随机性,风电场的输出功率会随机波动。功率波动会影响网络运行,因此需要进行平滑处理。为了缓解风电场的输出功率波动,本文提出了一种基于ADALINE(自适应线性NEuron)的四步协调控制技术,该技术使用了较小的BESS(电池储能系统)容量。首先,通过ADALINE对WFOP(风电场输出功率)进行在线跟踪。之后,在ADALINE输出上施加了两个最大波动限制。在第三和第四步骤中实现了充电反馈控制策略的两种状态。通过ADALINE进行的精确跟踪以及通过在状态反馈反馈控制策略执行的电池安全性能区域内保持BESS节省的能量水平,可以实现建议的协调控制技术中电池容量的减少。由真实数据运行的仿真结果证明,该方法的性能明显优于基本方法。 (C)2016 Elsevier Ltd.保留所有权利。

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