• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.971-976
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• 2014

In this paper, we proposed a low power algorithm using state transition ready method. The proposed algorithm defined a sleep state, a idle state and a run state for the task. A state transition occurring at the time due to the delay time created in order to reduce the power consumption state in the middle of each inserted into the ready state. The ready state considering a power consumption and a delay time in state transition. A scheduling step of performing the steps in excess of the increasing problems have the delay time is long. The power consumption increased for the operation step increase. A state transition from a sleep state with the longest delay time in operating state occurs when the state is switched by the time delay caused by the increase in operating time reduces the overall power consumption reduced. Experiments [6] were compared with the results of the power consumption. The experimental results [6] is reduced power consumption than the efficiency of the algorithm has been demonstrated.

• Journal of Power Electronics
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• v.19 no.4
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• pp.1054-1067
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• 2019

This paper systematically investigates the influence of device parameters spread on the current distribution of paralleled silicon carbide (SiC) MOSFETs. First, a variation coefficient is introduced and used as the evaluating norm for the parameters spread. Then a sample of 30 SiC MOSFET devices from the same batch of a well-known company is selected and tested under the same conditions as those on datasheet. It is found that there is big difference among parameters spread. Furthermore, comprehensive theoretical and simulation analyses are carried out to study the sensitivity of the current imbalance to variations of the device parameters. Based on the concept of the control variable method, the influence of each device parameter on the steady-state and transient current distributions of paralleled SiC MOSFETs are verified separately by experiments. Finally, some screening suggestions of devices or chips before parallel-connection are provided in terms of different applications and different driver configurations.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1625-1636
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• 2017

A power electronic transformer (PET) based on the cascaded H-bridge (CHB) and the isolated bidirectional DC/DC converter (IBDC) is capable of accommodating a large scale battery energy storage system (BESS) in the medium-voltage grid, and is referred to as a power electronic transformer based battery energy storage system (PET-BESS). This paper investigates the PET-BESS and proposes a coordinative control strategy for it. In the proposed method, the CHB controls the power flow and the battery state-of-charge (SOC) balancing, while the IBDC maintains the dc-link voltages with feedforward implementation of the power reference and the switch status of the CHB. State-feedback and linear quadratic Riccati (LQR) methods have been adopted in the CHB to control the grid current, active power and reactive power. A hybrid PWM modulating method is utilized to achieve SOC balancing, where battery SOC sorting is involved. The feedforward path of the power reference and the CHB switch status substantially reduces the dc-link voltage fluctuations under dynamic power variations. The effectiveness of the proposed control has been verified both by simulation and experimental results. The performance of the PET-BESS under bidirectional power flow has been improved, and the battery SOC values have been adjusted to converge.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1930-1939
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• 2015

Wind power planning aims to locate and size wind farms optimally. Traditionally, wind power planners tend to choose the wind farms with the richest wind resources to maximize the energy benefit. However, the capacity benefit of wind power should also be considered in large-scale clustered wind farm planning because the correlation among the wind farms exerts an obvious influence on the capacity benefit brought about by the combined wind power. This paper proposes a planning model considering both the energy and the capacity benefit of the wind farms. The capacity benefit is evaluated by the wind power capacity credit. The Ordinal Optimization (OO) Theory, capable of handling problems with non-analytical forms, is applied to address the model. To verify the feasibility and advantages of the model, the proposed model is compared with a widely used genetic algorithm (GA) via a modified IEEE RTS-79 system and the real world case of Ningxia, China. The results show that the diversity of the wind farm enhances the capacity credit of wind power.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.847-858
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• 2015

Control strategy and corresponding parameters have significant impacts on the overall technical and economic characteristics of composite energy storage systems (CESS). A better control strategy and optimized control parameters can be used to improve the economic and technical characteristics of CESS, and determine the maximum power and stored energy capacity of CESS. A novel coordinated control strategy is proposed considering the coordination of various energy storage systems in CESS. To describe the degree of coordination, a new index, i.e. state of charge coordinated response margin of supercapacitor energy storage system, is presented. Based on the proposed control strategy and index, an optimization model was formulated to minimize the total equivalent cost in a given period for two purposes. The one is to obtain optimal control parameters of an existing CESS, and the other is to obtain the integrated optimal results of control parameters, maximum power and stored energy capacity for CESS in a given period. Case studies indicate that the developed index, control strategy and optimization model can be extensively applied to optimize the economic and technical characteristics of CESS. In addition, impacts of control parameters are discussed in detail.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.1
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• pp.38-43
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• 2012

For safe and stable operations of power plants, it is essential to monitor closely crucial measurement values related to power plant trips. In this paper, an intelligent power plant operating state monitoring technique enabling the operating crew member to monitor conveniently the status of the important measurement values and to perceive almost instantly the significance of the implications of those measurement values is developed. The proposed technique is called a "POST(Plant Operating State Tracking) Chart" technique and provides the foundations in developing an intelligent and integrated power plant operating state monitoring support system called the "P-OASIS"(Plant Operation Assessment and Support Intelligent System). The P-OASIS is applied to a thermal power plant of 500[MW] capacity and exhibited impressive performances.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1049-1053
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• 1999

It is important to measuring and monitoring about state vectors of power system for precise operation control. All state vectors cannot be measured because it is economically disadvantageous, so that some state vectors are determined using state estimator. Determination of observability is a important precondition of power system state estimation because state estimation can be performed when given power system is observable. Recently as time-synchronization technique progress, using the PMU(Phasor Measurement Unit), state vector can be measured directly so that voltage phasor and current phasor measurements can be used for power system estimation. In this paper, observability algorithm is proposed to determinate the observability with real/reactive injection power measurements and real/reactive lineflow power measurements of existing measurement system and with phasor measurements of PMU. The jacobian matrix is newly composed for state estimation with measurements of added PMU, and state estimation is performed with least square estimatior. Comparison between state estimation result of existing measurement system and that of measurement system added PMU is presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.71-78
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• 2015

Since most education organizations such as Universities have a plenty of PCs, much electric power can be wasted if their power states are not managed properly. This paper introduces the RPM(Remote Power Management) software system implemented to reduce a waste of PC power in Universities. The System manager can monitor power state of all PCs in a University and turn off PCs or change power states of PCs to low power states. The RPM consists of three software modules. First, Power Controller, which is installed in each user PC, saves the power by changing low power state by utilizing low power algorithm proposed in this paper. Also it reports power state of its PC to Power Server on the state changed. Second, Power Server module gathers power state information of all PCs, stores them in a DB, and sends all or some parts of the information to Power Viewer whenever the manager asks. The manager can turn off or change a certain PC to low power state. We evaluated the performance of power saving for the RPM and the result showed achievement of 40% power saving.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.134-140
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• 2017

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1308-1316
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• 2017

The distributed maximum power point tracking (DMPPT) concept is widely adopted in photovoltaic systems to avoid mismatch loss. However, the high cost and complexity of DMPPT hinder its further promotion in practice. Based on the concept of DMPPT, this paper presents an integrated submodule level half-bridge stack structure along with an optimal current point tracking (OCPT) control algorithm. In this full power processing integrated solution, the number of power switches and passive components is greatly reduced. On the other hand, only one current sensor and its related AD unit are needed to perform the ideal maximum power generation for all of the PV submodules in any irradiance case. The proposal can totally eliminate different small-scaled mismatch effects in real-word condition and the true maximum power point of each PV submodule can be achieved. As a result, the ideal maximum power output of the whole PV system can be achieved. Compared with current solutions, the proposal further develops the integration level of submodule DMPPT solutions with a lower cost and a smaller size. Moreover, the individual MPPT tracking for all of the submodules are guaranteed.