• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.860-865
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• 2014

This paper proposes the method for determination of the capacities of ESS (Energy Storage System) and PCS (Power Conditioning System) for the peak load shaving based on the load data in the substation of urban railway. In addition, this paper analyze the actual measurement of loads in the substation of urban railway. The load of a weekday in the substation of urban railway is high around rush hours in the morning and evening, which is different from that of a normal substation. The required capacities of ESS and PCS become larger as the amount of peak load shaving is higher, and are affected from the patterns of daily load in the substation.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.981-987
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• 2017

In this paper, we estimate the economic benefits of Energy Storage Systems (ESSs) for peak load shaving in an urban railway substation using the annual cost. The annual investment cost of ESSs is estimated using Net Present Value (NPV) and compared with the cost reduction of electricity by the ESS. The optimal capacities of the battery and Power Converting System (PCS) are determined for peak load shaving. The optimal capacity of the ESS and the peak load shaving is determined to maximize the profit by the ESS. The proposed method was applied to real load data in an urban railway substation, and the results show that electric power costs can be reduced. Other aspects of the ESS, such as the lifetime and unit price of the battery, are also investigated economically.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1752-1758
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• 2014

This paper evaluates economic benefits of ESS (Energy Storage System) for peak load shaving in the substation of urban railway. For this purpose, the method to determine capacities of ESS and PCS (Power Conditioning System) for peak load shaving is proposed. Then the economic benefits of those devices are evaluated using net present value method. The proposed methods are applied to actual measurements of loads in the substation of urban railway. The results show that electric power costs can be reduced and the economic benefits of ESS for peak load shaving mainly depends on the price of battery.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.459-467
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• 2017

An urban railway power substation consists of three thyristor dual converters. Two converters are connected to up and down trolley line to supply the electric energy or feed the regenerative energy back to the distribution. When the two converters break down, the remaining converter is used in an emergency. One thyristor dual converter system (TDCS) manages the energy of two or three railway stations. If the TDCS fails, the trains stop operating. To solve the problem, this paper proposes the three parallel operation control algorithm of thyristor dual converter system using the emergency converter. The broken TDCS can be replaced by the emergency converter in other TDCS. The effectiveness of this proposed control is verified by simulation.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.157-161
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• 2008

The main purpose of this study is to analysis of urban MAGLEV vehicle for the Incheon International Airport Maglev railway, in the process of construction at the moment, in Korea. For analysis of urban MAGLEV, we have measurement power a special quality of MAGLEV operating the center science museum in Deajeon. 1) The power property related to urban MAGLEV vehicle demand on the Incheon International Airport Maglev railway track and substation capacity compared to the result given. 2) The optimum design of substation is determined based on the analysis. 3) The equipments of substation are determined based on the analysis. The result of measurement performance, therefore, enables us to reflect the good property, to the power supply design. The result of research performance, therefore, enables us to reflect the Power Supply System design for the stabilized and economized MAGLEV operation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.4
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• pp.333-337
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• 2010

This paper introduces an overall system design of a real-time monitoring system that monitors condition of urban railway AC/DC transformers, disconnecting switches, circuit breakers, regulators, and GIS (gas insulated switchgear). For effective diagnosis of urban railway facilities we developed optimized sensors and application technology. The proposed system is combined with wireless technology, implementing remote real-time monitoring of urban railway facilities. The derived real-time monitoring system for power facilities in urban railway substations will be applied not only to diagnose low voltage DC (direct current) railways but also to diagnose design of small power facilities of skyscrapers and apartments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.315-323
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• 2015

Nowadays, it is expected that mobility loads such as electric railways and electric vehicles will be penetrated gradually and affect on the power system stability by their load characteristics. Various researches have been carried out about electric vehicles for the recent decade though the load of electric railway could be forecasted because of the specified path and timetable, is a field with a long historic background. Some precise 5th polynomial equations are required to analyze the power system stability considering mobility load to be increased in the immediate future while the electric railway dispatching simulator uses load models with constant power and constant impedance for the system analysis. In this paper, seasonal urban railway load models are established as the form of 5th polynomial equations and substation load modeling methods are proposed merging railway station load models and general load models. Additionally, load management effects by the load modeling are confirmed through the case studies, in which seasonal load models are developed for Seoul Subway Line No. 2, Gyeongui Line and Airport Railroad and the substation load change is analyzed according to the railway load change.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.116-116
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• 2010

This paper introduces an comprehensive monitoring and management program for implementation of a real-time monitoring system that monitors condition of urban railway AC/DC transformers, disconnecting switches, circuit breakers, regulators, and GIS (Gas Insulated Switchgear). Especially, the system is applied to diagnose the overall condition of urban railway substations by sending acquired data through an OPC server to a database, effectively storing and monitoring conditions simultaneously. The above system is a management based system and is also applicable to small-scale systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1608-1614
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• 2014

Power demand forecasting is an important factor of the peak management. This paper deals with the 15 minutes ahead load forecasting problem in a DC urban railway system. Since supplied power lines to trains are connected with parallel, the load characteristics are too complex and highly non-linear. The main idea of the proposed method for the 15 minutes ahead prediction is to use the daily load similarity accounting for the load nonlinearity. An Euclidean norm with weighted factors including loads of the neighbor substation is used for the similar load selection. The prediction value is determinated by the sum of the similar load and the correction value. The correction has applied the neural network model. The feasibility of the proposed method is exemplified through some simulations applied to the actual load data of Incheon subway system.