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Artificial Neural Networks approach to the voltage sag classification

After PQ data of interest are obtained, a comprehensive PQ assessment can be carried out depending on the purpose of the study. This may include power system and equipment modeling verification, PQ problem mitigation and optimization, and data analysis [4,5]. In most cases, automated PQ assessment is desirable because manual analysis may be difficult to carry out due to lack of time and special expertise. Specialized software tools can make use of intelligent techniques to automate the PQ assessment for improved accuracy and efficiency [5]. This paper is focusing on automated detection and classification of voltage sags that may facilitate the overall PQ assessment. Intelligent techniques as fuzzy logic or neural networks have been utilized for developing PQ tools. Thus, a neural network approach will be undertaken in our case.