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Victor Mendes Ribeiro
Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora, MG
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Naiara da Silva Maia dos Santos
Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora, MG
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Eder Barboza Kapisch
Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora, MG
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Leandro Rodrigues Manso Silva
Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora, MG
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Carlos Augusto Duque
Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora, MG
Keywords:
Stockwell Transform, FPGA, Embedded processor, Power Quality
Abstract
Considering the smart grids (SGs) establishment scenario, where the presence of non-linear loads and new power generation forms become increasingly expressive, there is a potential for the emergence of new disturbances. Furthermore, considering the huge amount of data coming from smart meters, it is necessary to use novelty detection methods in voltage and current waveform signals, in order to preserve the relevant information and promote efficient storage of the data. The Stockwell Transform (ST) is a time-frequency distribution that has shown great ability to detect novelties related to stationarity changes in signals. Therefore, the present work describes the use of ST for the purpose of detecting novelties in Power Quality (PQ) signals. The implementation of this transform in FPGA is proposed through the use of a Soft- Core processor to optimize the hardware resources of the FPGA. In addition, a voice selection strategy is proposed in order to reduce the complexity of the algorithm, as well as reduce the processing time, while maintaining the detection capability.
