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An adaptive neuro-fuzzy inertia controller for variable-speed wind turbines

机译:变速风力涡轮机的自适应神经模糊惯性控制器

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A Variable-Speed Wind Turbine (VSWT) can serve as a good reservoir of Kinetic Energy (KE) for few seconds owing to wide operating rotor speed. Based on this fact, several approaches have been proposed to introduce synthetic inertial response in VSWT. Usually, this is accomplished by introducing an additional control loop at the outer most level of the control hierarchy. However, several key issues including the selection of control parameters and the effects of wind speed variations on the synthetic inertial support are not addressed. As a result, the KE reserve is severely under utilized. To address these concerns, in this work, a simple approach is proposed to control parameter selection which ensures the optimal use of available KE reserve. Further, to tackle the variable KE reserve, a comprehensive inertia controller using intelligent learning paradigm is designed. The proposed inertia controller can adapt to wind speed variations while providing optimum inertial response. Efficacy of the proposed approach is evaluated over the entire operating range of the VSWT. For further evaluation, wind speed data from NREL western wind integration is utilized. The results indicate that the proposed system is quite effective and can maintain an adequate performance over the entire operating range. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于转子的运行速度较宽,变速风力涡轮机(VSWT)可以在几秒钟内用作动能(KE)的良好储存库。基于这一事实,已经提出了几种在VSWT中引入合成惯性响应的方法。通常,这是通过在控制层次结构的最外层引入一个附加的控制循环来实现的。但是,没有解决几个关键问题,包括控制参数的选择以及风速变化对合成惯性支撑的影响。结果,KE储备被严重利用。为了解决这些问题,在这项工作中,提出了一种简单的方法来控制参数选择,以确保最佳地利用可用的KE储备。此外,为了解决可变的KE储备,设计了一种使用智能学习范例的综合惯性控制器。所提出的惯性控制器可以适应风速变化,同时提供最佳的惯性响应。在VSWT的整个操作范围内评估了所提出方法的有效性。为了进一步评估,利用了来自NREL Western Wind Integration的风速数据。结果表明,所提出的系统相当有效,并且可以在整个工作范围内保持足够的性能。 (C)2016 Elsevier Ltd.保留所有权利。

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