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Prediction of power system generator self-excitation using pattern recognition

机译:基于模式识别的电力系统发电机自励磁预测

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摘要

Power-system generators may experience self-excitation overvoltages due to certain contingencies. In an attempt to derive a novel self-excitation (SE) preventive scheme, the authors describe a prediction system based on pattern-recognition techniques. Several design approaches are explained. A hyperplane discriminant is used to define the predictor surface. An algorithm is developed to reduce the number of telemetered channels required and hence the complexity of the prediction system structure. Moreover, a fast corrective algorithm designed to provide security improvement action is explained. The system studied is the Manitoba Hydro northern AC collector system where SE is the operating problem of concern. The results obtained prove the effectiveness of the proposed prediction scheme.
机译:由于某些意外情况,电力系统发电机可能会遇到自激过电压。为了推导一种新颖的自激(SE)预防方案,作者描述了一种基于模式识别技术的预测系统。解释了几种设计方法。超平面判别式用于定义预测器表面。开发了一种算法来减少所需的遥测通道的数量,从而减少预测系统结构的复杂性。此外,解释了一种旨在提供安全性改进措施的快速纠正算法。研究的系统是Manitoba Hydro北部AC集热器系统,其中SE是值得关注的运行问题。获得的结果证明了所提出的预测方案的有效性。

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