Neural network based energy storage control for wind farms

B. Novakovic, R. Pashaie, A. Nasiri
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引用次数: 6

Abstract

One of the main issues related with the wind energy systems is the unpredictable and fluctuating nature of the extracted wind power. The combinations of different types of energy storage systems and control strategies have been proposed in the literature in order to improve the power quality coming from the wind turbines. In the current paper, a novel neural network based control system is proposed for the entire wind farm with distributed storage system. Storage is integrated in every wind turbine (WT) in the wind farm and proposed control system reduces the total output power fluctuations by using the available energy storage distributed among the wind turbines in a cooperative manner. For the verification of the proposed control method a Simulink model for a wind farm containing 100 wind turbines was developed and simulated.
基于神经网络的风电场储能控制
与风能系统相关的主要问题之一是提取的风力的不可预测性和波动性。为了提高风力发电机组的电能质量,文献中提出了不同类型的储能系统和控制策略的组合。本文提出了一种基于神经网络的分布式全风电场控制系统。将储能集成到风电场的每台风力机中,所提出的控制系统通过协作的方式利用分布在风力机之间的可用储能来减小总输出功率的波动。为了验证所提出的控制方法,开发了一个包含100台风力机的风电场的Simulink模型并进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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