• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.239-249
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• 2019

Recently, the Korean government has implemented a policy to expand renewable energy sources. Large-scale PV systems are being actively interconnected with the distribution system. On the other hand, when a large-scale PV system is installed and operated, the customer voltages could violate the allowable voltage limit due to reverse power flow of the PV system. To overcome these problems, an enhancement method for hosting the capacity of the PV system in a distribution system is being actively conducted. Therefore, to improve the hosting capacity of the PV system, this paper proposes a model of a reconfiguration of the distribution system, which is composed of three sections and three connections based on PSCAD/EMTDC S/W, and proposes an evaluation algorithm for the feeder reconfiguration to maximize an adaption of the PV system. In addition, this paper presents the optimal method of the feeder reconfiguration section to evaluate the maximum capacity of the PV system to keep customer voltages within the allowable voltage limits based on various operation scenarios, such as the capacity of a PV system and section of feeder reconfiguration. From the simulation results based on the PSCAD/EMTDC modeling and evaluation algorithm, it was confirmed that they are a useful and practical tool to enhance hosting the capacity of a PV system in a distribution system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.568-574
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• 2020

Recently, the installation of energy storage systems (ESSs) that have a range of functions, such as power stabilization of renewable energy sources, demand control, and frequency regulation, has been increasing annually. On the other hand, since the fire accident of ESS occurred at Gochang Power Test Center in August 2017, 29 fire accidents with significant property losses have occurred, including the Gyeongsan substation and Kunsan PV power plant. Because these fire accidents of ESS are arisen regardless of the season and capacity of ESS, an analysis of the fault characteristics in ESS is required to confirm the causes of the fire accidents accurately and ensure the safety of the ESS. This paper proposes the modeling of ESS using PSCAD/EMTDC S/W to identify the fault characteristics and ensure the safety of the ESS. From the simulation results of fault characteristics based on various scenarios, it is clear that the insulation of ESS may be breakdown due to the largely occurring CMV (common mode voltage). Furthermore, the CMV between the PCS and battery can be reduced, and the insulation breakdown of ESS can be prevented if an SPD (surge protect device) is installed in the battery and PCS sides, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.528-535
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• 2020

Recently, the protection coordination method of DC systems has been presented because renewable energy and distributed resources are being installed and operated in distribution systems. On the other hand, it is difficult to detect ground faults because there is no significant difference compared to a steady-state current in ungrounded IT systems, such as DC load networks and urban railways. Therefore, this paper formulates the detection principle of IMD (Insulation Monitoring Device) to use it as a protection coordination device in a DC system. Based on the signal injection method of IMD, which is analyzed by a wavelet transform, this paper presents an algorithm of detecting ground faults in a DC system in a fast and accurate manner. In addition, this paper modeled an IMD and an ungrounded DC system using the PSCAD/EMTDC S/W and performed numerical analysis of a wavelet transform with the Matlab S/W. The simulation results of a ground fault case in an ungrounded DC system showed that the proposed algorithm and modeling are useful and practical tools for detecting a ground fault in a DC system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.3
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• pp.183-196
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• 2010

Increasing human activity due to rapid economic growth and land use change alters the patterns of the Asian monsoon, which is key to crop yields in Asia. In this study, we tested the performance of regional climate model (RegCM3) by simulating important components of Indian summer monsoon, including land-ocean contrast, low level jet (LLJ), Tibetan high and upper level Easterly Jet. Three contrasting rain years (1994: excess year, 2001: normal year, 2002: deficient year) were selected and RegCM3 was integrated at 60 km horizontal resolution from April 1 to October 1 each year. The simulated fields of circulations and precipitation were validated against the observation from the NCEP/NCAR reanalysis products and Global Precipitation Climatology Centre (GPCC), respectively. The important results of RegCM3 simulations are (a) LLJ was slightly stronger and split into two branches during excess rain year over the Arabian Sea while there was no splitting during normal and deficient rain years, (b) huge anticyclone with single cell was noted during excess rain year while weak and broken into two cells in deficient rain year, (c) the simulated spatial distribution of precipitation was comparable to the corresponding observed precipitation of GPCC over large parts of India, and (d) the sensitivity experiment using NIMBUS-7 SMMR snow data indicated that precipitation was reduced mainly over the northeast and south Peninsular India with the introduction of 0.1 m of snow over the Tibetan region in April.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.47-65
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• 2014

VMS(Variable Message Sign) helps drivers to choose their path to destinations on roadways. Some types of VMS often provide traffic information with clearly visible and comprehensible graphical route diagrams. Currently many diagramed types of VMS are installed on urban arterial and highways. This type of VMS surely enhances drivers' ability to comprehend traffic route information while they are driving on the roadway. Nevertheless, some of them are presented with so much information and design elements and they sometimes lead to decline of drivers' comprehensible level for traffic information. Drivers would fail to decide their preferable route in this state of information overflow. The purpose of this paper is to develop a drivers preference model for effective design principle including size and height of displaying font, and the amount of information in the route diagram considering driving speed, sex and age of the driver. This model is developed using structural equation modeling techniques. This model considers driver's emotional factor and, human factor and design component of route diagram. To collect data, we built driving simulator which is able to replicate real driving condition. 72 people who participated in the simulation were selected considering gender and age. The developed model showed that the amount of information, and visibility are more influential factors to the drivers' preference of the route diagram on VMS than design elements such as the shape and the font of the diagram.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.

• Explosives and Blasting
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• v.40 no.3
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• pp.19-32
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• 2022

Hydrogen is a fuel having the highest energy compared with other common fuels. This means hydrogen is a clean energy source for the future. However, using hydrogen as a fuel has implication regarding carrier and storage issues, as hydrogen is highly inflammable and unstable gas susceptible to explosion. Explosions resulting from hydrogen-air mixtures have already been encountered and well documented in research experiments. However, there are still large gaps in this research field as the use of numerical tools and field experiments are required to fully understand the safety measures necessary to prevent hydrogen explosions. The purpose of this present study is to develop and simulate 3D numerical modelling of an existing hydrogen gas station in Jeonju by using handheld LiDAR and Ansys AUTODYN, as well as the processing of point cloud scans and use of cloud dataset to develop FEM 3D meshed model for the numerical simulation to predict peak-over pressures. The results show that the Lidar scanning technique combined with the ANSYS AUTODYN can help to determine the safety distance and as well as construct, simulate and predict the peak over-pressures for hydrogen refueling station explosions.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Journal of the Korea Concrete Institute
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• v.19 no.3
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• pp.359-366
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• 2007

Recently, analysis researches on durability are focused on chloride attack and carbonation due to increased social and engineering significance. Generally, chloride penetration and carbonation occur simultaneously except for in submerged condition and chloride behavior in carbonated concrete is evaluated to be different from that in normal concrete. Furthermore, if unavoidable crack occurs in concrete, it influences not only single attack but also coupled deterioration more severely. This is a study on analysis technique with system dynamics for chloride penetration in concrete structures exposed to coupled chloride attack and carbonation through chloride diffusion, permeation, and carbonation reaction. For the purpose, a modeling for chloride behavior considering diffusion and permeation is performed through previous models for early-aged concrete such as MCHHM (multi component hydration heat model) and MPSFM (micro pore structure formation). Then model for combined deterioration is developed considering changed characteristics such as pore distribution, saturation and dissociation of bound chloride content under carbonation. The developed model is verified through comparison with previous experimental data. Additionally, simulation for combined deterioration in cracked concrete is carried out through utilizing previously developed models for chloride penetration and carbonation in cracked concrete. From the simulated results, CCTZ (chloride-carbonation transition zone) for evaluating combined deterioration is proposed. It is numerically verified that concrete with slag has better resistance to combined deterioration than concrete with OPC in sound and cracked concrete.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.3
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• pp.219-229
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• 2018

This paper proposes Kalman Filter-based relative navigation algorithms for proximity tasks such as rendezvous/docking/cluster-operation of spacecraft using PSD Sensors and Infrared Beacon Modules. Numerical simulations are performed for comparative analysis of the performance of each relative-navigation technique. Based on the operation principle and optical modeling of the PSD Sensor and the Infrared Beacon Module used in the relative navigation algorithm, a measurement model for the Kalman filter is constructed. The Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF) are used as probabilistic relative navigation based on measurement fusion to utilize kinematics and dynamics information on translational and rotation motions of satellites. Relative position and relative attitude estimation performance of two filters is compared. Especially, through the simulation of various scenarios, performance changes are also investigated depending on the number of PSD Sensors and IR Beacons in target and chaser satellites.