Development of Data Cleaning and Integration Algorithm for Asset Management of Power System

Jae-Sang Hwang, Sung-Duk Mun, Tae-Joon Kim, Geun-Won Oh, Yeon-Sub Sim and Seung Jin Chang
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Jae-Sang Hwang: Korea Electric Power Corporation Research Institute, 105, Munji-ro, Yuseong-gu, Daejeon 34056, Korea
Sung-Duk Mun: Korea Electric Power Corporation Research Institute, 105, Munji-ro, Yuseong-gu, Daejeon 34056, Korea
Tae-Joon Kim: Korea Electric Power Corporation Research Institute, 105, Munji-ro, Yuseong-gu, Daejeon 34056, Korea
Geun-Won Oh: Department of Electrical Engineering, Hanbat National University, Daejeon 34158, Korea
Yeon-Sub Sim: Department of Electrical Engineering, Hanbat National University, Daejeon 34158, Korea
Seung Jin Chang: Department of Electrical Engineering, Hanbat National University, Daejeon 34158, Korea

Energies, 2022, vol. 15, issue 5, 1-18

Abstract: Asset management technology is rapidly growing in the electric power industry because utilities are paying attention to which of their aged assets should be replaced first. The global trend of asset management follows risk management that comprehensively considers the probability and consequences of failures. In the asset management system, the risk assessment algorithm operates by interfacing digital datasets from various legacy systems. In this study, among the various electric power assets, we consider transmission cable systems as a representative linear asset consisting of different segments. First, the configurations and characteristics of linear asset datasets are analyzed. Second, six types of data cleaning functions are proposed for extracting dirty data from the entire dataset. Third, three types of data integration functions are developed to simulate the risk assessment algorithm. This technique supports the integration of distributed asset data in various legacy systems into one dataset. Finally, an automatic data cleaning and integration system is developed and the algorithm could repeat the cleaning and integration process until data quality is satisfied. To evaluate the performance of the proposed system, an automatic cleaning process is demonstrated using actual legacy datasets.

Keywords: power system; transmission cable; data cleaning; asset management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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