• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1950-1957
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• 2015

Modern wind generators (WGs) are forced or encouraged to participate in frequency control in the form of inertial and/or primary control to improve the frequency stability of power systems. To participate in primary control, WGs should perform deloaded operation that maintains reserve power using speed and/or pitch-angle control. This paper proposes an optimization formulation that allocates the required reserve to WGs to maximize the kinetic energy (KE) stored in a wind power plant (WPP). The proposed optimization formulation considers the rotor speed margin of each WG to the maximum speed limit, which is different from each other because of the wake effects in a WPP. As a result, the proposed formulation allows a WG with a lower rotor speed to retain more KE in the WPP. The performance of the proposed formulation was investigated in a 100-MW WPP consisting of 20 units of 5-MW permanent magnet synchronous generators using an EMTP-RV simulator. The results show that the proposed formulation retains the maximum amount of KE with the same reserve and successfully increases the frequency nadir in a power system by releasing the stored KE in a WPP in the case of a disturbance.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.457-468
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• 2014

Recently, several approaches are proposed to support developing Self-Adaptive System. However, they do not provide the way to accept interaction between requirements and architecture. It makes difficult to judge the impact of changing requirements, handle quickly, and understand adaptation process for stakeholder. To overcome above problems, this paper suggests the interweaving method for providing traceability based on the relationship between requirements and architecture. This traceability allows tracing the impact of changing requirements, and it provides the rationale of architectural decision for advanced degree of understanding. Example shows the usefulness through developing process and changing process on Smart Grid domain.

• The Korean Journal of Physiology and Pharmacology
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• v.14 no.6
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• pp.427-433
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• 2010

This study was conducted to investigate the effects of extremely low frequency electromagnetic fields (EMF) on signal pathway in plasma membrane of cultured cells (RAW 264.7 cells and RBL 2H3 cells), by measuring the activity of phospholipase $A_2$ ($PLA_2$), phospholipase C (PLC) and phospholipase D (PLD). The cells were exposed to the EMF (60 Hz, 0.1 or 1 mT) for 4 or 16 h. The basal and $0.5\;{\mu}M$ melittin-induced arachidonic acid release was not affected by EMF in both cells. In cell-free $PLA_2$ assay, we failed to observe tbe change of $cPLA_2$ and $sPLA_2$ activity. Also both PLC and PLD activities did not show any change in the two cell lines exposed to EMF. This study suggests that the exposure condition of EMF (60 Hz, 0.1 or 1 mT) which is 2.4 fold higher than the limit of occupational exposure does not induce phospholipases-associated signal pathway in RAW 264.7 cells and RBL 2H3 cells.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.619-630
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• 2017

With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.

• Journal of Power Electronics
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• v.18 no.2
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• pp.482-491
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• 2018

The practical design methodology of a three-phase dual active bridge (3ph-DAB) converter applied to low voltage direct current (LVDC) applications is proposed by using a mathematical model based on the steady-state operation. An analysis of the small-signal model (SSM) is important for the design of a proper controller to improve the stability and dynamics of the converter. The proposed lead-lag controller for the 3ph-DAB converter is designed with a simplified SSM analysis including an equivalent series resistor (ESR) for the output capacitor. The proposed controller can compensate the effects of the ESR zero of the output capacitor in the control-to-output voltage transfer function that can cause high-frequency noises. In addition, the performance of the power converter can be improved by using a controller designed by a SSM analysis without additional cost. The accuracy of the simplified SSM including the ESR zero of the output capacitor is verified by simulation software (PSIM). The design methodology of the 3ph-DAB converter and the performance of the proposed controller are verified by experimental results obtained with a 5-kW prototype 3ph-DAB converter.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.155-161
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• 2015

The energy storage system is actively used as the widespread of smart grid. In the case of large scale EES, it can be efficiently controlled linked with BEMS or BAS. But, in the case of EES installed in a small sized household, it needs the help of the remote control system because it lacks the expert for controlling and operating of EES. In addition, in the case when the solar energy generation and EES are installed at the same time, a small sized EMS which can be efficiently controlled depending on the solar energy generation or electric power load is needed. In this paper, the EMS which can efficiently control the solar power generation as well as EES installed in a small sized household is implemented and its usefulness is verified through some experimental studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.4
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• pp.370-379
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• 2014

Recently, the interest in optical network with multifiber link is continuing to rise since the network traffic has been growing exponentially. However, growing traffic in network leads to increasing the energy consumption of the network equipment. In this paper, we propose a dynamic routing and wavelength assignment (RWA) algorithm based on V-like cost function and layered graph to improve energy efficiency in IP over WDM network with multifiber link. The V-like cost function is used to decide the fiber cost according to the number of used wavelengths. The layered graph with multifiber link is used to select the energy efficient route and wavelength. The proposed RWA algorithm is compared and analyzed with conventional algorithm in view of average power consumption and blocking probability through OPNET modeler.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.1-6
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• 2018

In smart grid an accurate load forecasting is crucial in planning resources, which aids in improving its operation efficiency and reducing the dynamic uncertainties of energy systems. Research in this area has included the use of shallow neural networks and other machine learning techniques to solve this problem. Recent researches in the field of computer vision and speech recognition, have shown great promise for Deep Neural Networks (DNN). To improve the performance of daily electric peak load forecasting the paper presents a new deep neural network model which has the architecture of two multi-layer neural networks being serially connected. The proposed network model is progressively pre-learned layer by layer ahead of learning the whole network. For both one day and two day ahead peak load forecasting the proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange (KPX).

• Journal of IKEEE
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• v.23 no.4
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• pp.1373-1380
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• 2019

In order to increase energy efficiency, developments of the advanced metering infrastructure (AMI) in the smart grid technology have recently been actively conducted. An essential part of AMI is analyzing power consumption and forecasting consumption patterns. In this paper, we analyze the power consumption and summarized the data errors. Monthly power consumption patterns are also analyzed using the k-means clustering algorithm. Forecasting the consumption pattern by each household is difficult. Therefore, we first classify the data into 100 clusters and then predict the average of the next day as the daily average of the clusters based on the deep neural network. Using practically collected AMI data, we analyzed the data errors and could successfully conducted power forecasting based on a clustering technique.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.81-93
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• 2016

Internet of Things (IoT) has been established in various industries and IoT technology is highlighted as a new value creation technology. Especially, Korean government has launched Manufacturing Innovation 3.0 Strategy for developing Smart Factory concept to improve national and corporate's competitiveness. This study tries to present new industry classification scheme considering 10 national key manufacturing industries. Based on the new scheme, 10 national main forces industries are categorized into 6 segments. We have conducted SWOT analysis to comprehend Korean IoT environment. Based on the analysis, we have positioned 6 segments at the strategic decision-making grid to analyze industries' IoT practical usage.