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Abstract
Diesel-Engine Driven Generators (DDGs) are a kind of distributed generation (DG) units and similar to other DGs, cause power quality disturbances in power system. Flicker is one of the most important power quality disturbances having bad effects on the sensitive loads. In DDGs, Inherent Torque Fluctuations (ITFs), Misfiring (MF) in various cylinders, Gearbox Tooth Crashing (GTC), governor and exciter errors in presence of the mentioned factors are some of the faults, which produce flicker. Therefore, it is necessary to recognize any faults causing flicker to prevent serious problem in DDGs. Also, identifying these factors is effective in accelerating process of repair and maintenance for DDGs. Therefore, in this paper firstly, all faults that cause flicker are modeled and simulated, then a pattern recognition method is presented for their detection. In the proposed method, Discrete Wavelet Transform (DWT) and Discrete S-Transform (DST) are used for feature extraction and Gram-Schmidt (GS) is used for feature selection. Afterwards, a classifier based on K-Nearest Neighbors (KNN) is used to detect the faults. Also, the impact of faults on flicker severity has been evaluated by short-term severity of flicker (Pst index).
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