使用二进制搜索算法对自励磁感应发电机进行稳态分析的改进和简化方法

COMPEL Pub Date : 2024-04-08 DOI:10.1108/compel-09-2023-0414
Essaki Raj R., Sundaramoorthy Sridhar
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引用次数: 0

摘要

目的 本文旨在开发一种基于二进制搜索算法(BSA)的改进方法,用于自励磁感应发电机(SEIG)的稳态分析。BSA 还与线性搜索算法(LSA)进行了比较,以显示 BSA 相对于 LSA 的优点。设计/方法/途径考虑了 SEIG 的所有参数,包括机器的不同铁芯损耗,以确保设置的预定性能值的准确性。采用了节点导纳法来简化发电机和负载的等效电路。在三相 240 V、5.0 A、2.0 kW SEIG 上获得的实验结果验证了所提出的方法,实验结果与相应的预测性能值非常吻合。原创性/价值 利用 SEIG 等效电路的节点导纳估算其单位频率 (a)、磁化电抗 (Xm) 和铁芯损耗电阻 (Rm) 的新型改进和简化技术。考虑到 SEIG 的铁芯损耗不断变化,可以提高预定性能的准确性。采用这些算法时只使用了简单的 MATLAB 编程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved and simplified approach for the steady-state analysis of self-excited induction generators using binary search algorithm

Purpose

This paper aims at developing an improved method, based on binary search algorithm (BSA) for the steady-state analysis of self-excited induction generators (SEIGs), which are increasingly used in wind energy electric conversion systems. The BSA is also compared with linear search algorithm (LSA) to bring out the merits of BSA over LSA.

Design/methodology/approach

All the parameters of SEIG, including the varying core loss of the machine, have been considered to ensure accuracy in the predetermined performance values of the set up. The nodal admittance method has been adopted to simplify the equivalent circuit of the generator and load. The logic and steps involved in the formulation of the complete procedure have been illustrated using elaborate flowcharts.

Findings

The proposed approach is validated by the experimental results, obtained on a three-phase 240 V, 5.0 A, 2.0 kW SEIG, which closely match with the corresponding predicted performance values. The analysis is shown to be easy to implement with reduced computation time.

Originality/value

A novel improved and simplified technique has been formulated for estimating the per unit frequency (a), magnetizing reactance (Xm) and core loss resistance (Rm) of the SEIG using the nodal admittance of its equivalent circuit. The accuracy of the predetermined performance is enhanced by considering the SEIG’s varying core loss. Only simple MATLAB programming has been used for adopting the algorithms.

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