• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.

• 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.

• Ocean Systems Engineering
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• v.13 no.1
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• pp.21-41
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• 2023

Decarbonization and energy transition can be considered as a main concern even for the oil industry. One of the initiatives to reduce emissions under studies considers the use of renewable energy as a complimentary supply of electric energy of the production platforms. Wind energy has a higher TRL (Technology Readiness Level) than other types of energy converters and has been considered in these studies. However, other types of renewable energy have potential to be used and hybrid concepts considering wind platforms can help to push the technological development of other types of energy converters and improve their efficiency. In this article, a preliminary hydrodynamic assessment of a new concept of hybrid wind and wave energy conversion platform was performed, in order to evaluate the potential of wave power extraction. A multiple OWCs (Oscillating Water Column) WEC (Wave Energy Converter) design was adopted for the analysis and some simplifications were adopted to permit using a frequency domain approach to evaluate the mean wave power estimation for the location. Other strategies were used in the OWC design to create resonance in the sea energy range to try to maximize the potential power to be extracted, with good results.

• Journal of Energy Engineering
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• v.12 no.3
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• pp.241-252
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• 2003

As more and more residential complexes will be developed in the future, this paper tries to establish the definitions and standards for the estimation of power demands in these areas and propose standards for the estimation of power demands for power companies and construction companies 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. Also, for general hospitals, sports facilities and government buildings of the non residential building category, metropolitan areas, where these facilities are concentrated, are surveyed and analyzed.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.10
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• pp.19-26
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• 2018

The purpose of this study was to analyze characteristics and to develop estimation model of IHG(Internal Heat Gain) from appliance in domestic apartment units. To do this, it was defined the source of IHG from appliance and the calculation method through the case study of international and domestic codes. And the equipment related datum such possession, usage or not, etc were collected through field survey in apartment units, and the appliances' electricity consumption were measured separately from overall electricity consumption. Annual electricity consumption value were calculated with field survey datum and appliances' electricity consumption measurement datum, and then IHG value was calculated by applying PHPP v9 method. And it was conducted correlation analysis between IHG value and the area for exclusive use, the number of occupants, and then the IHG from applianace estimation model was deducted with regression analysis. Finally, it was analyzed the present level and of the domestic code(The Building Energy Efficiency Rating System) comparing with the value of estimation model, and the various international codes(HERS, Building America, SAP).

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.55-63
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• 2014

Up to date, numerous studies on wireless sensor networks have been performed to overcome the Energy-Constraint of the sensor system. Existing schemes for estimating the residual energy have considered only voltage of sensor system. However battery performance in the real is affected by temperature and load. In this paper we introduce more accurate scheme, for the use in wireless sensor node, based on the interpolation of lookup tables which allow for temperature and load characteristics, as well as battery voltage.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1664-1673
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• 2016

Lithium rechargeable cells are used in many industrial applications, because they have high energy density and high power density. For an effective use of these lithium cells, it is essential to build a reliable battery management system (BMS). Therefore, the state of charge (SOC) estimation is one of the most important techniques used in the BMS. An appropriate modeling of the battery characteristics and an accurate algorithm to correct the modeling errors in accordance with the simplified model are required for practical SOC estimation. In order to implement these issues, this approach presents the comparative analysis of the SOC estimation performance using equivalent electrical circuit modeling (EECM) and noise suppression technique (NST) in three representative $LiCoO_2/LiFePO_4/LiNiMnCoO_2$ cells extensively applied in electric vehicles (EVs), hybrid electric vehicles (HEVs) and energy storage system (ESS) applications. Depending on the difference between some EECMs according to the number of RC-ladders and NST, the SOC estimation performances based on the extended Kalman filter (EKF) algorithm are compared. Additionally, in order to increase the accuracy of the EECM of the $LiFePO_4$ cell, a minor loop trajectory for proper OCV parameterization is applied to the SOC estimation for the comparison of the performances among the compared to SOC estimation performance.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.508-513
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• 2009

Significant air temperature increases in urban areas are known as the heat island phenomenon in a global scale. Therefore, we use numerical model in order to analyze quantitative effects by using new & renewable energy on the heat island phenomenon in urban area. The present study quantitatively analyzes the Urban Heat Island Effects, Energy-Saving Effects, and Environmental Load Decrease Effect along New and Renewable Energy Application which is 10% of the Building Energy Consumption.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.45-53
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• 2018

Demand for essential resources including water, energy and food is rapidly increasing due to climate change, population growth and urbanization. To solve this problem, the concept of water-energy-food nexus has been introduced, and many countries have been trying to acquire the Nexus technology that can maximize the efficiency by analyzing the interconnection between resources. In this regard, this study attempted to estimate the probable maximum water thermal energy in the dam based on the water-energy nexus concept. The estimation of the probable maximum water thermal energy was implemented to monthly water storage of the largest dams in the four major river systems. As a result of analyzing the estimated monthly water thermal energy from 2000 to 2016, Soyang River dam has the largest probable maximum water thermal energy, and Sumjin River dam has the smallest. However, the probable maximum water thermal energy was small in common between March and April, between September and October due to the small temperature difference between the ambient air and the dam water. Also, according to the characteristics of the dam, Daecheong dam and Soyang River dam were beneficial for supplying water thermal energy for heating, and Sumjin River dam and Andong dam were advantageous for supplying water thermal energy for cooling. Our findings can be useful to realize the water-energy-food nexus by increasing the utilization and value of water resources as well as expanding the roles and functions of dams as a starting point to use dam water thermal energy.