• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.349-352
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• 2008

The most concerning issue in these days is the energy crisis by increasing threat of global warming and depletion of natural resources. In the situations, the Plug-in Hybrid Electric Vehicle (PHEV) is drawing attention from many countries for the next generation's car which has higher fuel efficiency and lower environmental impact. This paper presents simulation results about the limit capacity of central power-grid which doesn't have enough surplus electric power for charging PHEVs. Therefore, this paper also presents a smart charging system that can charge the PHEVs with a function of distributing demands of charging. The smart charging system is an agent facility between the government and consumer, which can recommend the best time to charge the battery of PHEVs by the lowest energy cost. This function of choosing time-slots is the technical system for the government which wants to control the consumption rate of electric power for PHEVs. Finally, this paper presents the economic feasibility of PHEVs from the two kinds of price system, midnight electric price and home electric price.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.25-28
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• 2021

In this paper, we studied smart phone RF wireless charging with 5.8-GHz microwave wireless power receiver. The dc output of the receiver connected to super capacitor and DC-DC converter for charging a smart phone. This configuration stably supplies 5V and current for charging it. Studies show that the more receivers are used at close range, the higher the received voltage values and the larger the capacity of the super capacitor, the longer the charging time. The present 5.8-GHz 1W wireless power transmission system is not enough for charging a smartphone mainly due to the lack of current of the receiver.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.136-139
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• 2021

In this paper, we studied the charging characteristics of high-capacity supercapacitor with high current for RF wireless charging system for smart phone charging. The dc output of the RF-DC receiver is connected to supercapacitor after which is connected to DC-DC converter for charging a smart phone. This configuration stably supplies voltage and current for charging it. Studies show that the higher charging current use, the rapidly shorter the charging time of supercapacitor is. The currents of 2A, 10A and 27A were used for charging supercapacitors. The charging time was measured for 3000F, 6000F, 12000F supercapacitors which is parallelly connected with 3000F supercapacitors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.10-17
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• 2014

The Jeju Special Self-Government Provincial Government has made the plan penetrating gradually electric vehicles(EVs) in the Jeju Special Self-Government Province(Jejudo). However the effects of EVs penetration on the electrical grid of the Jejudo is not reported. In this paper the yearly electric energy consumed by the EVs was calculated and the effects of the EV penetration on the peak power of the grid were analyzed in the Jejudo for the future 10 years, and we hope that our study results will help the governors realize the EVs penetration plan in the Jejudo. The calculation results show that the rate of the electric energy used by the EVs will become to 2.9% at its maximum at the 2017 year when the penetration rate of EVs in passenger cars becomes 10%, and the rate of the electric energy consumed by the EVs will become to 9.4% at its maximum at the 2020 year when the penetration rate of EVs in passenger cars becomes 30%. The concepts of smart-charging capacity and 100%-valley-filling charging capacity of the grid were defined and calculated for the Jeju Grid, and the grid was analyzed to have the sufficient EV charging capacity until the 2022 year.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.343-352
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• 2017

IEC62541, known as OPC-UA, is a standard communication protocol for Smart Grid (SG) and Smart Factory application platform. It was accepted as an IEC standard (IEC62541) in 2011 by IEC TC57, and is extending range of application as collaborating with other standrads. The government's policies to popularize EVs ("Workplace Charging Challenge"), the number of Electric vehicle which try to be charging in the factory is expected to increase. In this situation, indiscreet and uncontrolled EV charging can lead to some problems, such as excess of the peak demand capacity. Therefore, EVs, which is charging in SFs, must be monitoring and controlling to avoid and reduce peak demand. However, the standards for EVs charging differ from the standards for SFs. In other words, to increase the ease of use for drivers, and reduce risk for enterprise, we have needs of study to develop the protocols or to provide interoperability, for EVs charging in SFs. This paper deals with a EV charging management platform installing in a smart factory. And this platform can be easily integrated as part of SF management software. The main goal of this paper is to implement EV management system based on IEC61851 and IEC62541.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1759-1768
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• 2018

The energy density, power density and ohm resistance of battery change significantly as results of battery aging, which lead to decrease in the accuracy of the equivalent model. A parameter identification method of the equivale6nt circuit model with 3 R-C branches based on the test database of battery life cycle is proposed in this paper. This database is built on the basis of experiments such as updating of available capacity, charging and discharging tests at different rates and relaxation characteristics tests. It can realize regular update and calibration of key parameters like SOH, so as to ensure the reliability of parameters identified. Taking SOH, SOC and T as independent variables, lookup table method is adopted to set initial value for the parameter matrix. Meanwhile, in order to ensure the validity of the model, the least square method based on variable forgetting factor is adopted for optimizing to complete the identification of equivalent model parameters. By comparing the simulation data with measured data for charging and discharging experiments of Li-ion battery, the effectiveness of the full life cycle database and the model are verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.513-521
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• 2012

With the advent of smart grid, distribution network charges have been one of keystones of ongoing deregulation and privatization in power industries. This paper proposes a new charging methodology to allocate the existing distribution network cost with an aim of reflecting the true cost and benefit of network customers, especially of distribution generator (DG). The proposed charging methodology separates distribution network costs due to the respective real and reactive power flows. The costs are then allocated to network users according to each charge for the actual line capacity used and available capacity. This distribution network charging model is able to provide the economic signals to reward network users who are contributing to better power factors, while penalizing customers who worsen power factors. The proposed method is shown on IEEE 37 bus system for distribution network, and then the results are validated through the comparison with the MW-Miles and MVA-Miles methods. The charges derived from the proposed method can provide appropriate incentives/penalties to network customers to behave in a manner leading to a better network condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.859-864
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• 2015

This paper analyzes the impact of Plug-in Electric vehicles(PEVs) on power demand and voltage change when PEVs are connected to the domestic distribution system. Specifically, it assesses PEVs charging load by charging method in accordance with PEVs penetration scenarios, its percentage of total load, and voltage range under load conditions. Concretely, we develop EMTDC modelling to perform a voltage distribution analysis when the PEVs charging system by their charging scenario was connected to the distribution system under the load condition. Furthermore we present evaluation algorithm to determine whether it is possible to adjust it such that it is in the allowed range by applying ULTC when the voltage change rate by PEVs charging scenario exceed its allowed range. Also, detailed analysis of the impact of PEVs on power distribution system was carried out by calculating existing electric power load and additional PEVs charge load by each scenario on new-town in Korea to estimate total load increases, and also by interpreting the subsequent voltage range for system circuits and demonstrating conditions for countermeasures. It was concluded that total loads including PEVs charging load on new-town distribution system in Korea by PEVs penetration scenario increase significantly, and the voltage range when considering ULTC, is allowable in terms of voltage tolerance range up to a PEVs penetration of 20% by scenario. Finally, we propose the charging capacity of PEVs that can delay the reinforcement of power distribution system while satisfying the permitted voltage change rate conditions when PEVs charging load is connected to the power distribution system by their charging penetration scenario.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.