UNBALANCED LOAD FLOW WITH HYBRID WAVELET TRANSFORM AND SUPPORT VECTOR MACHINE BASED ERROR-CORRECTING OUTPUT CODES FOR POWER QUALITY DISTURBANCES CLASSIFICATION INCLUDING WIND ENERGY

• Видавець: National Technical University "Kharkiv Polytechnic Institute" and State Institution “Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine”
• Дата: 2019
• Автори: Rahmani, Ala eddine, Slimani, Linda, Bouktir, Tarek
• Формат: Стаття
• Мова: English
• Опубліковано: National Technical University "Kharkiv Polytechnic Institute" and State Institution “Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine” 2019
• Теми: unbalanced load flow; wavelet transform (WT); support vector machines (SVM); power quality disturbance; wavelet energy; 621.3; несбалансированный поток нагрузки; вейвлет-преобразование (WT); машины опорных векторов (SVM); нарушение качества электроэнергии; энергия вейвлета
• Онлайн доступ: http://eie.khpi.edu.ua/article/view/2074-272X.2019.6.09

Purpose. The most common methods to design a multiclass classification consist to determine a set of binary classifiers and to combine them. In this paper support vector machine with Error-Correcting Output Codes (ECOC-SVM) classifier is proposed to classify and characterize the power quality disturbances such as harmonic distortion, voltage sag, and voltage swell include wind farms generator in power transmission systems. Firstly three phases unbalanced load flow analysis is executed to calculate difference electric network characteristics, levels of voltage, active and reactive power. After, discrete wavelet transform is combined with the probabilistic ECOC-SVM model to construct the classifier. Finally, the ECOC-SVM classifies and identifies the disturbance type according to the energy deviation of the discrete wavelet transform. The proposed method gives satisfactory accuracy with 99.2% compared with well known methods and shows that each power quality disturbances has specific deviations from the pure sinusoidal waveform, this is good at recognizing and specifies the type of disturbance generated from the wind power generator.