• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.279-286
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• 2021

Recently, the effort of enterprises are visualized to correspond for 4th industrial revolution and climate change. Reaching the operation of industrial facilities are one of these efforts and is actively progressing under identical condition between real and virtual world through introduction of cyber-physical system (CPS). However, the problem on no unified definition for CPS still exists. Thus, in this paper, we review the previous concept of CPS. We propose new concept of CPS with four sections such as real world section, communication section, virtual world section and management section. We also propose definite concept by classifying the layer of each section. In order to confirm the possibility of application for proposed concept of CPS, we applied simple motor. We compare the result for torque between real motor and virtual motor. Finally we confirm that the applicability of proposed concept of CPS is very high.

• Journal of Power Electronics
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• v.17 no.2
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4145-4164
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• 2016

Energy harvesting is an increasingly attractive source of power for cellular networks, and can be a promising solution for green networks. In this paper, we consider a cellular network with power beacons powering multiple mobile terminals with microwave power transfer in energy beamforming. In this network, the power beacons are powered by grid and renewable energy jointly. We adopt a dual-level control architecture, in which controllers collect information for a core controller, and the core controller has a real-time global view of the network. By implementing the water filling optimized power allocation strategy, the core controller optimizes the energy allocation among mobile terminals within the same cluster. In the proposed green energy cooperation paradigm, power beacons dynamically share their renewable energy by locally injecting/drawing renewable energy into/from other power beacons via the core controller. Then, we propose a new water filling optimized green energy cooperation management strategy, which jointly exploits water filling optimized power allocation strategy and green energy cooperation in cellular networks. Finally, we validate our works by simulations and show that the proposed water filling optimized green energy cooperation management strategy can achieve about 10% gains of MT's average rate and about 20% reduction of on-grid energy consumption.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.8
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• pp.685-692
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• 2007

This paper describes the development procedure of GUI Program for the automated generation of airfoil performance table used in helicopter comprehensive code. Considering commercialization, the program is developed based on the Windows operating system. In addition, it is aimed to enhance user's convenience by including embedded postprocessor which enables real-time display of calculation procedure and grid system. Using the validated CFD code, the aerodynamic analyses are automated for a given range of Mach number and angles of attack. The computational grid system is designed to generate automatically once the surface coordinates are given. Mixed-Language scheme is employed in order to combine the CFD code in Fortran with C++ based GUI program, which makes the time-consuming code conversion unnecessary.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• Spatial Information Research
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• v.21 no.5
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• pp.63-72
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• 2013

This paper analyzed the flood propagation characteristics of each flood elevation due to failure of embankment in Muju Namdae Stream using recursive call algorithm. A flood propagation order by the flood elevation was estimated by setting destruction point at Beonggu and Chasan small dam through recursive call algorithm and then, the number of grids of each flood propagation order and accumulated inundation area were calculated. Based on the flood propagation order and the grid size of DEM, flood propagation time could be predicted each flood elevation. As a result, the study could identify the process of flood propagation through distribution characteristic of the flood propagation order obtained from recursive call algorithm, and could provide basic data for protection from flood disaster by selecting the flood vulnerable area through the gradient pattern of the graph for accumulated inundation area each flood propagation order. In addition, the prediction of the flood propagation time for each flood water level using this algorithm helped provide valuable information to calculate the evacuation path and time during the flood season by predicting the flood propagation time of each flood water level.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.42-47
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• 2016

Due to advances such as photovoltaic power generation and energy storage system, energy self-consumption smart home system in which energy management system is built and energy is generated in house has been actively researched. In particular, due to the instability of the grid after the Fukushima nuclear accident, home system in which generating electricity from photovoltaic, storing and using it in energy storage system was commercialized in Japan. While subsidizing renewable energy projects through a combination of solar and energy storage systems in North America and Europe has expanded home installation. In this paper, we describe development of self-consumption smart home system which is connecting photovoltaic system and energy storage system in home area network and operating it based on real-time price. We implemented automated self-consumption home in which optimizing the use of energy from the power grid with minimal user's intervention.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.1
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• pp.94-100
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• 2015

Coronal mass ejection (CME) released due to solar flare explosion cause geomagnetic disturbance. The induced current by massive geomagnetic disturbance can cause damage to the transformer. The calculated geoelectric field is a major parameter of the geomagnetically induced current (GIC). The method applying a Fourier transform has a high accuracy but it needs all data measured for 24 hours. And the other method applying a integral equation can calculate in real time but it requires to check an accuracy. To reduce the gap between the calculated results of two methods, it adjusts the integration section. As a result, the correlation between two calculated geoelectric fields is high, and the event time and direction of the calculated current is the same as that of the measured current, and it's accuracy rate is above 92 percent.

• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.23-30
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• 2017

OpenADR is a national standard communication protocol of demand response service. OpenADR uses XML message, called a payload, to support logical transaction of demand response service. For this purpose, OpenADR defines a XML element as transaction identifier which is called requestID. Unfortunately, OpenADR 2.0b profile specification describes some information about requestID but, it is not enough for understanding properly. Ambiguous definition of payload transaction makes vulnerabilities of implementing VEN & VTN and confuses mapping OpenADR 2.0b protocol into other smart grid protocols. Therefore, this paper redefines payload transaction to solve an ambiguous information of OpenADR 2.0b profile specification, proposes a model of analyzing payload transaction, and shows how to detect a payload transaction vulnerability in real-world.