Investigating the Effect of Outliers in Historical-Data on Grey Prediction Model for Power System State Estimation

This paper puts forth a closer look into the impact of having multiple outliers in the historical data, which are fed to the Grey Prediction Model named GM(1,1) for the purpose of predicting the value of current missing datum. The mentioned miss is majorly caused by sudden, momentary and unforeseen...

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Bibliographic Details
Published in2023 3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET) pp. 1 - 5
Main Authors Samajdar, Prabal, Halder nee Dey, Sunita
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.12.2023
Subjects
Analytical models
Current measurement
Data models
Historical Data
Outliers
Power systems
Predictive models
State estimation
WLS
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Summary:This paper puts forth a closer look into the impact of having multiple outliers in the historical data, which are fed to the Grey Prediction Model named GM(1,1) for the purpose of predicting the value of current missing datum. The mentioned miss is majorly caused by sudden, momentary and unforeseen failures of measuring as well as telemetering equipment. Once the predicted datum is ready, it is able to aid the State Estimation (SE) of Power System. Weighted Least Squares (WLS) method is applied here as the SE technique.
DOI:10.1109/ICEFEET59656.2023.10452191