• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.409-413
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• 2016

The 500 MW rated steam turbine model in coal fired power plant is developed to be used for validation and verification of controller rather than for the education of operator. The valve, steam turbine, reheater and generator are modeled and integrated into the simulator. And the data from the plant heat balance diagram are used for estimation of the model parameters together with actual operating data. It is found that the outputs of model such as pressure, temperature and speed are similar to the operating ones. So, it is expected that the developed model will play a very big role in controller development.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.139-146
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• 2012

In the server cluster environment, one of the ways saving energy is to control server's power according to traffic conditions. This is to determine the ON/OFF state of servers according to energy usage of data center and each server. To do this, we need a way to estimate each server's energy. In this paper, we use a software-based power consumption estimation model because it is more efficient than the hardware model using power meter in terms of energy and cost. The traditional software-based power consumption estimation model has a drawback in that it doesn't know well the computing status of servers because it uses only the idle status field of CPU. Therefore it doesn't estimate consumption power effectively. In this paper, we present a CPU field based power consumption estimation model to estimate more accurate than the two traditional models (CPU/Disk/Memory utilization based power consumption estimation model and CPU idle utilization based power consumption estimation model) by using the various status fields of CPU to get the CPU status of servers and the overall status of system. We performed experiments using 2 PCs and compared the power consumption estimated by the power consumption model (software) with that measured by the power meter (hardware). The experimental results show that the traditional model has about 8-15% average error rate but our proposed model has about 2% average error rate.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1721-1726
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• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.51-57
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• 2018

In this paper, we investigate the impact of channel estimation error on the D2D power control algorithm. In the previous work, D2D power control algorithm has been proposed under the assumption that the channel between the transmitter and the corresponding receiver is perfectly estimated. In reality, the channel estimation error is more often the case. The first question is that the power control algorithm designed for perfect channel estimation is still valid under the channel estimation error environment ? The second question is, if it is not valid, what could be the possible remedy for the channel estimation error ? In this paper, to answer the first question, we investigate the impact of the channel estimation error on the power control algorithm. We first review the D2D power control algorithm designed for perfect channel estimation. Then, we model the channel estimation error. Finally, we summarize the main results observed from the analysis of the simulation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.595-596
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• 2008

we present a technique of power estimation for LCD panels using regression model. We extract and model two different power sources in LCD panels, those are gray-scale power and additional power of parasitic capacitors for charge sharing effect with inversion scheme. To model the power source, we use curve fitting and approximation. The results of proposed technique show that an average accuracy of estimation is above 98%.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1317-1326
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• 1999

As the integration ratio and operation speed increase, it has become an important problem to estimate the dissipated power during the design procedure as a method to reduce the TTM(time to market). This paper proposed a prediction model to estimate the maximum dissipated power of a CMOS logic gate. This model uses a calculational method. It was formed by including the characteristics of MOSFETs of which a CMOS gate consists, the operational characteristics of the gate, and the characteristics of the input signals. As the modeling process, a maximum power estimation model for CMOS inverter was formed first, and then a conversion model to convert a multiple input CMOS gate into a corresponding CMOS inverter was proposed. Finally, the power model for inverter was applied to the converted result so that the model could be applied to a general CMOS gate. For experiment, several CMOS gates were designed in layout level by $0.6{\mu}m$ layout design rule. The result by comparing the calculated results with those from HSPICE simulations for the gates showed that the gate conversion model has within 5% of the relative error rate to the SPICE and the maximum power estimation model has within 10% of the relative error rate. Thus, the proposed models have sufficient accuracies. Also in calculation time, the proposed models was more than 30 times faster than SPICE simulation. Consequently, it can be said that the proposed model could be used efficiently to estimate the maximum dissipated power of a CMOS logic gate during the design procedure.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2520-2527
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• 2000

An improved transition density propagation method for power estimation is proposed. The power estimation for the zero delay model is a proper criteria for the.lower boutldlIry for power consumption. A transition propagation method, including the zero delay model as a lower boundary for power stimation was studied. However, there were some redundancy factors in the process of transition density propagation. Hence this paper will explore the transition density propagation behavior to eliminate the redundancy factors and present theirriprQved estimation methodology for the signal transition density. The experiments show that the proposed method has comparably better estimation accuracy than the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.4
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• pp.148-155
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• 1986

This paper presents a new decoupled power system state estimation method. The decoupling is achieved via simple linear transformation on power measurements in contrast with the modified fast decoupled state estimation method which assumes decoupling by direct negligence of the off-diagonal blocks of the observation functions. The new estimation method is compared with the modified decoupled state estimation method against IEEE-14 bus model power system and 25 bus model power system in several system conditions. It is observed that the proposed method shows better convergence performance and filtering performance than a modified fast decoupled state estimation.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.311-319
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• 2013

Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.