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• W3210259234 abstract "Penetration of renewable energies has changed the way of managing energy and monitoring the quality of the power supply. New types of disturbances have appeared because of uncontrolled connections and non-linear loads, whose stochastic behaviour triggers the need for global indicators capable of dealing with big data in terms of compression and scalability so that to extract useful information regarding network’s status and the prevailing disturbances for risk assessment. We propose a permanent and continuous measurement strategy through a virtual instrument that incorporate higher-order statistics that assesses the voltage waveform from a statistical point of view; using two-dimensional graphics and computing changes in the probability density funtion in the voltage waveform in the point of common coupling (PCC). Being suitable for both power quality and reliability the campaign results also conclude that graphics for the industrial reports that incorporate the skewness and kurtosis measurements helps characterizes the deviations of the voltage supply waveform, extracting the individual customers’ pattern traces, and compressing data, and the signal behaviour under normal operating continuous from both time and spatial considerations. The approach fosters a continuous and robust performance as needed in rel time campaigns in the modern network. Consequently, it can be used as a probabilistic approach to assess the risk of deviation of the voltage quality." @default.
• W3210259234 created "2021-11-08" @default.
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• W3210259234 date "2021-09-29" @default.
• W3210259234 modified "2023-09-27" @default.
• W3210259234 title "Instrument for Power Quality monitoring using Higher-Order Statistics 2D planes" @default.
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• W3210259234 doi "https://doi.org/10.1109/amps50177.2021.9586011" @default.
• W3210259234 hasPublicationYear "2021" @default.
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