Optimum active power tracking based control of brushless doubly-fed reluctance generator tied to renewable microgrid

A. Parida, Manish Paul
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Abstract

Among all the existing wind energy generators (WEG), a brushless doubly-fed reluctance generator (BDFRG) is the better option in terms of maintenance cost and constructional simplicity. For more adaptability, the efficiency of the BDFRG can be improved through proper control mechanisms. Therefore, this paper presents an optimum active power tracking-based control technique for BDFRG for minimum losses. Copper loss of the machine is considered to be the objective function for the proposed optimization technique. However, one issue found to be the major in all the existing controllers is the accuracy of sensor less control of the BDFRG. Therefore, this paper proposes an accurate model reference adaptive system (MRAS) based sensor less mechanism for computation of BDFRG secondary winding flux position. The no sensitivity of the proposed technique to the machine parameter variation and hence the accuracy, catch-on-fly, and non-inclusion of integrator and differentiators and hence less burden on the processor makes the proposed scheme robust. The control scheme is practically implemented with a 2.5 kW BDFRG using MATLAB/Simulink platform.
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基于有功功率跟踪的无刷双馈磁阻发电机与可再生微电网的优化控制
在现有的所有风能发电机(WEG)中,无刷双馈磁阻发电机(BDFRG)是维护成本和结构简单的最佳选择。为了提高适应性,可以通过适当的控制机制来提高无刷双馈磁阻发电机的效率。因此,本文提出了一种基于有功功率跟踪的 BDFRG 最佳控制技术,以实现最低损耗。机器的铜损被视为所提优化技术的目标函数。然而,所有现有控制器都存在一个主要问题,即 BDFRG 的传感器控制精度较低。因此,本文提出了一种基于精确模型参考自适应系统(MRAS)的少传感器机制,用于计算 BDFRG 次级绕组磁通位置。所提出的技术对机器参数变化不敏感,因此精度高、可随时捕捉、不包含积分器和微分器,从而减轻了处理器的负担,使所提出的方案具有鲁棒性。该控制方案通过 MATLAB/Simulink 平台在一台 2.5 kW BDFRG 上实际实现。
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