http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Jung, Hosung,Kim, Hyungchul,Chang, Sang-Hoon,Kim, Joorak,Min, Myung-Hwan,An, Tae-Pung,Kwon, Sung-Il The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.3
Generally, an autotransformer(AT) feeding system consists of double tracks, up and down, with the trolley wire and feeder wire of the up and down tracks connected in the sectioning post(SP). Consequently, load current or fault current flows on two tracks based on catenary impedance characteristics, making it difficult to estimate catenary impedance accurately. This paper presents a technique for the estimation of catenary impedance using boosting current compensation based on the current division characteristics of an AT feeding system to improve the operation performance of impedance relay. To verify the technique, we model an AT feeding system through a power analysis program (PSCAD/EMTDC) and simulate various operation and fault conditions. Through the simulation, we confirmed that the proposed technique has estimated catenary impedance with a similar degree of accuracy to the actual catenary impedance
Hosung Jung,Hyungchul Kim,Sang-Hoon Chang,Joorak Kim,Myung-Hwan Min,Tae-Pung An,Sung-Il Kwon 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.3
Generally, an autotransformer(AT) feeding system consists of double tracks, up and down, with the trolley wire and feeder wire of the up and down tracks connected in the sectioning post(SP). Consequently, load current or fault current flows on two tracks based on catenary impedance characteristics, making it difficult to estimate catenary impedance accurately. This paper presents a technique for the estimation of catenary impedance using boosting current compensation based on the current division characteristics of an AT feeding system to improve the operation performance of impedance relay. To verify the technique, we model an AT feeding system through a power analysis program (PSCAD/EMTDC) and simulate various operation and fault conditions. Through the simulation, we confirmed that the proposed technique has estimated catenary impedance with a similar degree of accuracy to the actual catenary impedance.
Jung, Seungmin,Lee, Hansang,Kim, Kisuk,Jung, Hosung,Kim, Hyungchul,Jang, Gilsoo The Korean Institute of Electrical Engineers 2013 Journal of Electrical Engineering & Technology Vol.8 No.5
Owing to the consistent increase in energy efficiency issues, studies for improving regenerative energy utilization have been receiving attention in the Urban DC railway systems, where currently, the utilization of regenerative energy is low due to the lack of a specific plan for using this energy. The regenerative energy in railway systems has a low efficiency problem which results in the increase of the catenary voltage and a possibility to create problems to the electrical devices connected to the system. This paper deals with the power integration of large urban railway subsystems to improve regenerative energy utilization where the railway subsystems are integrated with other railway subsystems to improve the energy efficiency. Through the case studies, to find the realistic effect of integrated operation, the Seoul Metro subsystems, namely Line 5 and Line 7, has been applied. Also, evaluation for the electricity cost saving has been performed by using KEPCO electricity cost table.
Bank Funding Structure and Lending under Liquidity Shocks : Evidence from Korea
Hosung Jung,Dongcheol Kim 한국재무학회 2013 한국재무학회 학술대회 Vol.2013 No.11
This paper examines the relation between bank funding structure and lending to firms during periods of liquidity shocks. We analyze this relation by using quarterly loan panel data of all commercial banks in Korea, as well as their borrowing firms. We find that when liquidity shocks are severe, banks generally reduce their lending, but banks with a high core funding ratio tend rather to increase their lending to firms during periods of market-wide liquidity shocks and thereby the reduction in lending due to liquidity shocks is offset. This tendency is stronger in banks that maintain relationship banking with the firms. However, these findings are valid only for large banks. Our findings could provide some important policy implications for financial supervisory authorities seeking some regulatory policies on liquidity as in Basel III.
An Alternative System GMM Estimation in Dynamic Panel Models
Hosung Jung,Hyeog Ug Kwon,Gyehyung Jeon 한국계량경제학회 2015 JOURNAL OF ECONOMIC THEORY AND ECONOMETRICS Vol.26 No.2
The system GMM estimator in dynamic panel data models which combines two sets of moment conditions, i.e., for the differenced equation and for the model in levels, is known to be more efficient than the first-difference GMM estimator. However, an initial optimal weight matrix is not known for the system estimation procedure. Therefore, we suggest the use of ‘a suboptimal weight matrix’ which may reduce the finite sample bias whilst increasing its asymptotic efficiency. Our Monte Carlo experiments show that the small sample properties of the suboptimal system estimator are much more reliable than any other conventional system GMM estimator in terms of bias.
Jung Hosung 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.1
This paper proposes the optimal charging and discharging scheduling algorithm of energy storage systems based on reinforcement learning to save electricity pricing of an urban railway system in Korea. Optimization is done through reinforcement learning of charging and discharging schedule of energy storage systems according to the unit of electricity pricing rates as well as a reduction of peak power demand to save electricity pricing. To do this, modeling of urban railway systems including energy storage systems, electricity pricing rates, and changes in rates according to operations of energy storage systems are carried out. Reinforcement learning for an agent is also done to reduce peak power demand through DQN algorithm. Operation data of actual lines of urban railways operating with energy storage systems are utilized for learning. For this reinforcement learning, about 399(45.3%) incorrect data are removed and 481(54.7%) normal data are extracted. Through the reinforcement learning, maximum peak power demand is reduced by a targeted amount, 100 kW, from 2,982.4 kW to 2,882.4 kW. When the peak power demand is under 2,600 kW, charging at times when the power rate is cheaper and discharging at times when the power rate is more expensive are carried out, thus saving the total electricity pricing.