Pires, Y., Santos, A., Borges, J., Carvalho, A., Vinicius, M., Nunes, A., Santoso, S., Klautau, A.: A framework for evaluating data mining techniques applied to power quality.
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Witten, I., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, 2nd edn. Hastie, T., Tibshirani, R., Friedman, J.: The elements of statistical learning. Vasilic, S.: Fuzzy Neural Network Pattern Recognition Algorithm for Classification of the Events in Power System Networks. In: Engineering Society Summer Meeting, pp. Santoso, S., Power Lamoree, J.D.: Power quality data analysis: From raw data to knowledge using knowledge discovery approach. In: IEEE Press Series on Power Engineering (2000) Power Engineering Society Winter Meeting 1, 632–634 (2002)īollen, M.H.J.: Understanding power quality problems: Voltage sags and interruptions. Kitayama, M., Matsubara, R., Izui, Y.: Application of data mining to customer profile analysis in the power electric industry. In: Advanced Data Mining and Applications (ADMA), pp. Zhang, L., Chen, S., Hu, Q.: Dynamic shape modeling of consumers’ daily load based on data mining. This process is experimental and the keywords may be updated as the learning algorithm improves.īell, S., McArthur, S., McDonald, J., et al.: Model-based analysis of protection system performance. These keywords were added by machine and not by the authors. Results with different preprocessing (e.g., wavelets) and learning algorithms (e.g., decision trees and neural networks) are presented, which indicate that neural networks outperform the other methods. To circumvent the current lack of labeled data, the Alternative Transients Program (ATP) simulator was used to create a public comprehensive labeled dataset. These faults are responsible for the majority of the disturbances and cascading blackouts. This work focuses on automatic classification of faults in transmission lines. A major problem is to extract useful information from the currently available non-labeled digitized time series. However, the companies in this area still face several difficulties to benefit from data mining. Data mining can play a fundamental role in modern power systems.
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