In this paper, a method to generate large amounts of Electric Arc Furnace (EAF) currents with harmonics simulating the actual EAF operation characteristics to be used with deep learning (DL) applications of harmonic estimation is investigated. For this purpose, the behavior of the EAF current harmonics is examined in statistical terms using the field data collected at a transformer substation supplying an EAF plant. Then, a significantly larger amount of EAF current data is generated using the statistics mimicking the real EAF behavior to train the DL-based harmonic estimator. The outcomes of ...Daha fazlası
In this article, a new approach to compensate both the response and reaction times of active power filters (APF) for special cases of highly time-varying harmonics and interharmonics of electric arc furnace (EAF) currents is proposed. Instead of using the classical approach of taking a window of past current samples and analyzing the data, future samples of EAF currents are predetected using a deep learning (DL)-based method and then analyzed, which provides the opportunity to make real-time analysis. This can also serve the needs of other possible APF applications. Two different methods for p ...Daha fazlası