• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.125-126
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• 2010

In this paper, a novel multiple output converter using quasi load is proposed. Conventional multiple output converters using multi-winding transformer has poor output voltage regulations. To solve this problem, there are many proposals like post regulation method, weighted control method, and etc. However, the post regulation method regulates output voltage tightly but its conduction loss and cost are increased. And the weighted control can achieve high efficiency and low cost but its regulation is not enough. To solve these problems, this paper proposes a novel multiple output converter using quasi load. The proposed method uses a quasi load which acts like an active dummy load for tight regulation but there is rarely increase of loss and cost. The proposed method is verified by hardware test by two output(24V and 15V) flyback type converter.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.12
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• pp.601-608
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• 2001

The ever increasing density of adjustable speed drives(ASD) device with non-linear operating characteristics has been to put tremendous harmonic stress on end user's electrical application. All ASD controllers which employ solid state power devices cause harmonic currents in the source side line. This paper describes harmonic problems for use of ASD. In order to investigate the effect of harmonics caused by using of nonlinear load at the low voltage system, we fixed up simple load model and measured the voltage and current waveforms. Measurement results show that additional operation of linear load at the parallel bus with nonlinear load such as ASD is helpful to the reduction of harmonic influence.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.835-837
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• 1996

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network(Back-propagation) is proposed. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time. For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor mentioned above. The one day ahead forecast errors are about 1.4% for absolute percentage average error.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.559-563
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• 1991

Permanent magnet synchronous motor (PMSM) is receiving increased attention for servo drive applications in recent years because of its high torque to inertia ratio, superior power density and high efficiency. Vector-controlled PMSM has the same operating characteristics as separately excited dc motor. The drive system of servo motor is requested to have an accurate response for the speed reference and a quick recovery for the disturbance such as load torque. However the dynamics of PMSM drive change greately by parameter variations. Morever, when the unkown and inaccessible disturbances are imposed on PMSM, the drive system is given a significant effect by them. As a result, the drive system with both a fast drive performance and a reduced sensitivity to parameter variations is requested. In this paper, the robust control system of PMSM with torque feedforward using load torque observer is presented. In the proposed system, load torque is estimated by the reduced order observer, and the robust control system against load torque variation is realized using the torque feedforward. Moreover, the design of speed controller with the torque observer is discussed. Simulation results show that the proposed method is effective for suppression of parameter variations and load disturbance.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.530-532
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• 2002

The contracted electric power and the demand factor of customers are used to predict the peak load in distribution transformers. The conventional demand factor was determined more than ten years ago. The contracted electric power and power demand have been increased. Therefore, we need to prepare the novel demand factor that appropriates at present. In this paper, we modify the demand factor to improve the peak load prediction of distribution transformers. To modify the demand factor, we utilize the 169 data acquisition devices for sample distribution transformers. The peak load currents were measured by the case studies using the actual load data, through which we verified that the proposed demand factors were correct than the conventional factors. A newly demand factor will be used to predict the peak load of distribution transformers.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.2
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• pp.150-157
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• 2012

This paper presents CAN-based parallel-operation and load-sharing techniques for the communication server power supply. With the load information obtained through CAN communication, each modules performs its current control independently and the power unbalance caused by impedance differences of converter modules can be reduced. In conventional method, slave modules are controlled by master module. On the other hand, the proposed load share algorithm uses the Multi-Master method. Therefore, accurate load sharing can be accomplished by the reference structure of each module's average current. Each converter has two stages and it is separated into PFC, which is responsible for harmonic regulation, and LLC resonant converter, which controls output voltage. To verified the performance of the proposed method, two 2KW prototypes has been implemented and experimented.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.244-251
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• 2013

This paper presents a study the change of the load profile on the power system by the charging impact of electric vehicles (EVs) in 2020. The impact of charging EVs on the load demand is determined not only by the number of EVs in usage pattern, but also by the number of EVs being charged at once. The charging load is determined on an hourly basis using the number of the EVs based on different scenarios considering battery size, model, the use of vehicles, charging at home or work, and the method of charging, which is either fast or slow. Focusing on the impact of future load profile in Korea with EVs reaching up 10 and 20 percentage, increased power demand by EVs charging is analyzed. Also, this paper analyzes the impact of a time-of-use (TOU) tariff system on the charging of EVs in Korea. The results demonstrate how the penetration of EVs increases the load profile and decreases charging demand by TOU tariff system on the future power system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2419-2435
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• 2023

Command and control networks(C2N) exhibit evident multi-network interdependencies owing to their complex hierarchical associations, interleaved communication links, and dynamic network changes. However, the existing command and control networks do not consider the effects of dependent nodes on the load distribution. Thus, we proposed a command and control networks load allocation strategy based on interdependence strength. First, a new measure of interdependence strength was proposed based on the edge betweenness, which was followed by proposing the inter-layer load allocation strategy based on the interdependence strength. Eventually, the simulation experiments of the aforementioned strategy were designed to analyze the network invulnerability with different initial load capacity parameters, allocation model parameters, and allocation strategies. The simulation indicates that the strategy proposed in this study improved the node survival rate of the interdependent command and control networks model and successfully prevented cascade failures.