• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.86-88
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• 2003

New cities and industrial complexes are being developed actively according to the government's policy. To determine the size of investment, number of power lines and substations for stable power supply to newly developed industrial complexes, the accurate estimation of power demand is necessary. "The standards for the estimation of power demands in newly developed residential and industrial complexes" established by KEPCO in 1991 have been used up to now. But the background for the estimation of power demands is weak and the accuracy has not been verified. Also, it has been passed above 10 years since their establishment and the social & economic situations have changed a lot, which requires an urgent revision. Through this survey and analysis of existing areas, new standards that will enable more accurate estimation of power demands in new cities and industrial complexes to be developed in the future are established by calculating the some kinds of power demand factors.

• 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.

• 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 Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1535-1542
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• 2007

HTS (High Temperature Superconducting) Power devices has the several useful characteristics from the technical and economical viewpoint. Possible application to the utility industry have been widely discussed in various research projects. For the successful introduction of HTS power devices into power system, establishing a proper R&D and marketing strategies through estimating the future market size are necessary. However, quantitative estimates of how well HTS power devices will serve their markets have been lacking. In this paper, we propose a estimation methodology of future market size for HTS power divices such as cable, transformer, generator, and motor, and also evaluate the future international and domestic market size by using proposed methodology.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.49-52
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• 2020

Since power plant is an important system to provide electricity, it is necessary to monitor it in order to operate safely. Much information related with machine diagnosis exists in written form instead of digital data. So, it causes difficulties of analyzing and finding solutions. Rulebased expert system can provide flexible and effective solutions to users. In this paper, Recursive Bayesian Estimation is applied in order to increase accuracy of solutions.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.77-79
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• 2003

New cities and industrial complexes are being developed actively because of the government policies aiming population distribution and vitalization of construction industry. To determine the investment amount, number of power lines and substations for stable power supply to newly developed residential and industrial complexes, accurate estimation of power demand is necessary. This paper propose standards for the estimation of power demands for power company and construction company to settle the debates surrounding this issue. Through a survey and analysis of existing areas, new standards that will enable more accurate estimation of power demands in new cities complexes to be developed in the future are established by calculating the average load density, load factor, utilization factor by area, use and building size after dividing the facilities into building type and the areas into the areas planned to be developed and the areas not yet planned to be developed.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.2 s.344
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• pp.42-50
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• 2006

Owing to the development of semiconductor processing technology, high density complex circuits can be integrated in a System-on-Chip (SoC). However, increasing energy consumption becomes one of the most important limiting factors. Power estimation at the early stage of design is essential, since design changes at lower levels may significantly lengthen the design period and increase the cost. In this paper, logic level circuits ire levelized and several levels are selected to build power model tables for efficient power estimation. The proposed techniques are applied to a set of ISCAS'85 benchmark circuits to illustrate their effectiveness. Experimental results show that significant improvement in estimation accuracy and slight improvement in efficiency are achieved when compared to those of a well-known existing method. The average estimation error has been reduced from $9.49\%\;to\;3.84\%$.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.2
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• pp.156-162
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• 2011

The preliminary design stage of helicopters consists of various operations and in each operation design several detailed analysis tasks are needed. The analysis tasks include performance and the required power estimation. In helicopter design, those are usually carried out by adopting the momentum theory. In this paper, an explicit form of computational analysis based on the blade element theory and uniform/non-uniform inflow model is developed. The other motivation of the present development is to obtain trim and required power estimation for various helicopter configurations. Sectional and hub loads, power, trim, and flapping equations are derived by using a symbolic tool. Iterative computations are carried out till convergence is achieved in the blade response, inflow, and trim. The predictions regarding the trim and power estimation turn out to be correlated well with the experimental results. The effect of inflow is further investigated. It is found that the present prediction for the lateral cyclic pitch angle is improved with the non-uniform inflow model as compared to that by the uniform inflow model. The presently improved trim and power estimation will be useful for future helicopter sizing and performance analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.767-773
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• 2014

The carrier-to-noise power ratio is a key parameter for determining the reliability of PVT (Position, Velocity, and Time) solutions which are obtained by a GNSS (Global Navigation Satellite System) receiver. It is also used for locking a tracking loop, deciding the re-acquisition process, and processing advanced navigation in the receiver subsystem. The representative carrier-to-noise power ratio estimation schemes are the narrowband-wideband power ratio method (NW), the MM (Moment Method), and Beaulieu's method (BL). The NW scheme is the most classical one for commercial GNSS receivers. It is often used as an authoritative benchmark for assessing carrier-to-noise power estimation schemes. The MM scheme is the least biased solution among them, and the BL scheme is a simpler scheme than the MM scheme. This paper focuses on the less biased estimation with low complexity when the residual phase noise remains, then proposes a novel carrier-to-noise power ratio estimation scheme with low complexity for GNSS receivers. The asymptotic bias of the proposed scheme is derived and compared with others, and the simulation results demonstrate that the complexity of the proposed scheme is lowest among them, while the estimation performance of the proposed scheme is similar to those of the BL and MM schemes in normal and high gained reception environments.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.376-383
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• 2012

A number of scientific researches are currently being conducted on the potential health hazards of power frequency electric and magnetic field (EMF). There exists a non-objective and psychological belief that they are harmful, although no scientific and objective proof of such exists. This possible health risk from ELF magnetic field (MF) exposure, especially for children under 17 years of age, is currently one of Korea's most highly contested social issues. Therefore, to assess the magnetic field exposure levels of those children in their general living environments, the personal MF exposure levels of 436 subjects were measured for about 6 years using government funding. Using the measured database, estimation formulas were developed to predict personal MF exposure levels. These formulas can serve as valuable tools in estimating 24-hour personal MF exposure levels without directly measuring the exposure. Three types of estimation formulas were developed by applying evolutionary computation methods such as genetic algorithm (GA) and genetic programming (GP). After tuning the database, the final three formulas with the smallest estimation error were selected, where the target estimation error was approximately 0.03 ${\mu}T$. The seven parameters of each of these three formulas are gender (G), age (A), house type (H), house size (HS), distance between the subject's residence and a power line (RD), power line voltage class (KV), and the usage conditions of electric appliances (RULE).