Jung-Wook Woo

Jung-Wook Woo


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 January 2020 in Applied Sciences
Verified
Journal Article
Open access
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TKTaeyong Kim
Taeyong Kim
YLYoun-Jung Lee
Youn-Jung Lee
SSSimpy Sanyal
Simpy Sanyal
JWJung-Wook Woo
Jung-Wook Woo
ICIn-Hyuk Choi
In-Hyuk Choi
JYJunsin Yi
Junsin Yi
Porcelain insulators should be exchanged periodically, but their lifetime is not clearly defined. One factor that affects service life is corrosion occurring at the pin and cap—each of which is made of iron with a zinc coating. A number of porcelain insulators used for different lengths of time in different locations are gathered, and the corrosion mechanisms of the cap and pin are investigated. The corrosion mechanism of the cap is mainly galvanic corrosion while that of the pin is primarily electrolytic and crevice corrosion as well as galvanic corrosion. Although time is an important factor in corrosion, it is found that corrosion is more influenced by geographical factors. Since the amount of acid rain and sea salt—each of which causes rapid rusting—is dependent on geographical factors, the location of where porcelain insulators are installed should be considered when predicting their lifetime. Theoretically, if there is only galvanic corrosion occurring, the expected lifetime is 56 years in an industrial area when the zinc coating has a thickness of 75 µm. Previous articles dealing with aging have predicted the maximum lifetime of porcelain insulators used in Korea to be approximately 30 years. To prolong the lifetime of porcelain insulators, further study is required in which the use of zinc alternatives, or waterproof coatings (in addition to the zinc coating), could be examined.

23 July 2018 in Energies
Verified
Journal Article
Open access
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BJByoung-Soo Joo
Byoung-Soo Joo
JWJung-Wook Woo
Jung-Wook Woo
JLJeong-hun Lee
Jeong-hun Lee
IJInjoo Jeong
Injoo Jeong
JHJungmin Ha
Jungmin Ha
SKSoobae Kim
Soobae Kim
Geomagnetic disturbances have the potential to impact the operation of electric power systems, and thus the assessment of their impacts is required as the first step for secure power system operations. While the effects of the disturbances have been observed primarily at higher latitudes, geomagnetic problems are also observed at mid and low latitude locations, in particular including neighboring countries to Korea such as China and Japan. This paper deals with the assessment of impact of geomagnetic disturbances on Korean electric power systems. For the assessment, the geoelectric fields induced by the geomagnetic disturbances are calculated using geomagnetic data measured over the past 20 years in order to quantify the strength of geomagnetic events in Korea. Then, the geomagnetic currents on the grid driven by the geoelectric fields are computed. Finally, the increased reactive power absorption in high voltage transformers is analyzed and accordingly the change of system voltage magnitudes is identified to evaluate whether the system maintains the voltage stability. The systematic study concludes that during a strong geomagnetic disturbance, the Korean electric power system satisfies the associated standards in the U.S. and maintains system stability.

20 December 2019 in Applied Sciences
Verified
Journal Article
Open access
PDF file
ICIn-Hyuk Choi
In-Hyuk Choi
JKJa-Bin Koo
Ja-Bin Koo
JWJung-Wook Woo
Jung-Wook Woo
JSJu-Am Son
Ju-Am Son
DBDo-Yeon Bae
Do-Yeon Bae
Taekeun OhTaekeun Oh
Taekeun Oh
Frequency response signals have been used for the non-destructive evaluation of many different structures and for the integrity evaluation of porcelain insulators. However, it is difficult to accurately estimate the integrity of porcelain insulators under various environmental conditions only by using general frequency response signals. Therefore, this study used a method that extracted several features that can be derived from the frequency response signal and reduced their dimensions to select features suitable for the evaluation of the soundness of porcelain insulators. The latest machine learning techniques were used to identify correlations and not for basic feature analyses. Two machine learning models were developed using the support vector machine and ensemble methods in MATLAB. Both models showed high reliability in distinguishing between normal and defective porcelain insulators, and they could visualize the distribution area of the data by extracting quantitative values and applying machine learning, rather than simply verifying the frequency response signal.