The energy sector’s investment aims to ensure a continuous, reliable, and quality supply of electrical energy imposed by the electricity regulatory agency with maximum economic-financial balance. The analysis of missing data and outliers is made on the three-phase voltage, current, and power factor of 459 time series of real feeders shows that most missing data are three-phase, however, with a significant amount of single and dual-phase loss that can be filled by the proportion between phases. Hence, the challenge is to fill multiple weeks of missing three-phase data, and for that, the use of the standard curve for each day of the week is proposed. Therefore, this library proposes a method of preprocessing, and missing data imputation using the unbalanced characteristic between phases, interpolation, and the normalized scaled standard weekday curve.
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pip install MVDataProcessingimport MVDataProcessing as mvp
#Simple process example. Check the console for explanation.
#Run with plot=True to visualize plot and then with plot=False to check performance.
mvp.ShowExampleSimpleProcess(plot=True)import MVDataProcessing as mvp
#NSSC process example. Check the console for explanation.
#Run with plot=True to visualize plot and then with plot=False to check performance.
mvp.ShowExampleNSSCProcess(plot=True)Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
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