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Predicting the Damage of Distribution System by Strong Wind
  • Oh, Seongmun ;
  • Jung, Jaesung ;
  • Jufri, Fauzan Hanif ;
  • Choi, Min Hee
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Publication Year
2019-05-01
Journal
2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019, pp.3970-3974
Keyword
Climate changeDamage predictionDistribution systemGrid resilienceStrong wind
Mesh Keyword
Damage predictionDistribution systemsElectric power companyEquipment failuresGrid resiliencePearson correlation analysisStrong windsWeather parameters
All Science Classification Codes (ASJC)
Artificial IntelligenceComputer Networks and CommunicationsEnergy Engineering and Power TechnologyRenewable Energy, Sustainability and the EnvironmentElectrical and Electronic EngineeringControl and Optimization
Abstract
This paper presents the methodology to predict the strong wind-related damage in the distribution system. For this, weather data and distribution system failure data are collected from the Meteorological Administration and an electric power company in South Korea respectively. Then, these datasets are integrated to analyze a relationship between weather and equipment failures in the distribution system. The prediction model is developed based on a typical regression model using the highly-correlated weather parameters selected by Pearson correlation analysis. Furthermore, two models which called the divided and combined models are developed to enhance an accuracy of prediction based on the natural disaster standard. To verify the algorithm, the results of the developed model are compared with the basic regression model by using the actual data in the strong windy day.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36458
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074948396&origin=inward
DOI
https://doi.org/10.1109/isgt-asia.2019.8881415
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8864995
Type
Conference
Funding
ACKNOWLEDGMENT This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20172410100040).
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Jung, Jaesung 정재성
Department of Electrical and Computer Engineering
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