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Proper selection of Doubly Fed Induction Generator Wind Turbine Using Several Optimization Techniques

机译:Proper selection of Doubly Fed Induction Generator Wind Turbine Using Several Optimization Techniques

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Renewable energy resources are future sponsors for electrical power generation all over the world. Wind energy is one of the most common used resources for electrical power generation. One of the mostly used wind turbine technology is Doubly Fed Induction Generator (DFIG) based wind turbine. In this paper, Electrical energy generated from the DFIG wind turbine is maximized for any linearized estimated wind speed profile. Different optimization techniques (Harmony Search algorithm (HSA), Invasive Weed Optimization (IWO) and Interior Point Nonlinear programming) are used to select optimal wind turbine speed rating to maximize electrical generated energy. Mathematical Curve fitting for the DFIG wind turbine's wind speed-output power characteristics curve is carried out. The curve fitting helps the classical method to deal with the problem without needing to build a complex mathematical model. Two case studies with two different linearized estimated wind speed profiles are made for examination of optimal wind turbine speed rating selection. After completion of optimization process, Results for different optimization techniques are compared. IWO gives the best optimal wind turbine speed rating with maximum generated energy for the wind turbine.
机译:可再生能源资源是世界各地电力发电的未来赞助商。风能是电力发电最常见的使用资源之一。其中一个主要使用的风力涡轮机技术是基于辅助的诱导发电机(DFIG)的风力涡轮机。在本文中,从DFIG风力涡轮机产生的电能最大化用于任何线性化估计的风速型材。使用不同的优化技术(和声搜索算法(HSA),侵入杂草优化(IWO)和内部点非线性编程)用于选择最佳风力涡轮机速度额定值以最大化电气产生的能量。进行了DFIG风力涡轮机的风速输出功率特性曲线的数学曲线拟合。曲线拟合有助于经典方法处理问题而不需要构建复杂的数学模型。两种案例研究具有两种不同的线性化估计风速型材,用于检查最佳风力涡轮机速度额定值选择。完成优化过程后,比较不同优化技术的结果。 IWO提供了最佳的风力涡轮机速度等级,具有最大的风力涡轮机产生的能量。

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