• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.443-450
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• 2017

Nowadays, Power Line Communication (PLC) is gaining high attention from industry and electric supply companies for the services like demand response, demand side management and Advanced Metering Infrastructure (AMI). The reliable services to consumers using PLC can be provided by utilizing an efficient PLC channel for which sophisticated channel modeling is very important. This paper presents characterization of a Low Voltage (LV) access network for Narrowband Power Line Communications (NB-PLC) using transmission line (TL) theory and a Simulink model. The TL theory analysis not only includes the constant parameters but frequency selectivity is also introduced in these parameters such as resistance, conductance and impedances. However, the proposed Simulink channel model offers an analysis and characterization of capacitive coupler, network impedance and channel transfer function for NB-PLC. Analysis of analytical and simulated results shows a close agreement of the channel transfer function. In the absence of a standardized NBPLC channel model, this research work can prove significant in improving the efficiency and accuracy of NB-PLC communication transceivers for Smart Grid communications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1697-1704
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• 2017

As the power grid has been changed to a smart grid, existing power technologies are evolving into convergence technology through interdisciplinary research. According to the government policy to increase the proportion of renewable energy to 20% by 2030, the speed seems to be accelerating. This study analyzes the relationship between research technologies in order to grasp research trends of smart grid technology. To this end, we analyze the relationship between keywords extracted from topic modeling using social network analysis methodology. This is because, in the field where interdisciplinary research such as smart grid is active, each research topic is not independent, but research technologies emerging in one topic coexist in different topics, and linkage between research technologies can be important information. Therefore, this study can contribute to the analysis of research trend as it can be used as a package tool together with a topic modeling methodology.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.584-587
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• 1997

In this paper, we present a transmission constraints modeling of carrier relay signal over ATM network. Since teleprotection system, which is used for protecting power transmission lines using telecommunications, has strict transmission delay constraints, it is a important problem to transmit teleprotection signals in future utilities' ATM networks when utilites' communications are integrated. Therefore, we considered the transmission constraints of carrier relay signal over ATM network and the transmission model system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.127-137
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• 2000

This paper presents a novel neural based controller which controls the water level of the nuclear power plant steam generator. The controller consists of a model reference feedback linearization controller and a PI controller for stabilizing the feedback linearization controller. The feedback linearization controller consists of a neural network model and an inversing module which uses the neural network model for computing the control input to the steam generator. We chose Piecewise Linearly Trained Network(PLTN) and Recurrent Neural Netwrok(RNN) for an approximator of the plant and used these approximators in calculating the input from the feedback linearization controller. Combining the above two controllers gives a result of better performance than the case which uses only a PI controller Each control result of PLTN and RNN is given.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.421-423
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• 2007

The paper used to the Neral Netwok for a forecasting conservation system A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. The true power and advantage of neural network lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Netwok is will play an important role for insulation diagnosis system of real site GIS and power equipment using $SF_6$ gas.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1428-1429
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• 2007

The paper used to the Neral Netwok for a forecasting conservation system. A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. The true power and advantage of neural network lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Netwok is will play an important role for insulation diagnosis system of real site GIS and power equipment using Dry-Air gas.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.127-131
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• 2005

The paper addresses modeling and analysis of a grid-connected photovoltaic generation system (PV system). PSCAD/EMIDC. an industry standard simulation tool for studying the transient behavior of electric power system and apparatus. is used to conduct all aspects of model implementation and to carry out extensive simulation study. An equivalent circuit model of a solar cell has been used for modeling solar array. A PWM voltage source inverter (VSI) and its current control scheme have been implemented. A maximum power point tracking (MPPT) technique is employed for drawing the maximum available energy from the PV array. Comprehensive simulation results are presented to examine PV array behaviors and PV system control performance in response to irradiation changes. In addition, dynamic responses of PV array and system to network fault conditions are simulated and analysed

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.494-501
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• 1999

In this research, ANN modeling method of SMES unit is developed for stability analysis, and the optimal site is selected to maximize stabilization effect of SMES unit. The ANN is trained by learning data which is obtained through the application of complex test function into the traditional mathematical mode. In order to verify the validity of proposed modeling method, fault data of sample power system is applied to both the traditional and the ANN models. When the response of traditional and proposed models are compared, the average error for the active and reactive power are 2.51[%], and 0.24[%], respectively. From the comparison, the relevance of proposed method is validated. For the transient stability analysis, an application method of the proposed model is presented, and the transient stability performance index, which describes system stabilization effect of SMES at disturbance, is also suggested, and optimal site selection method of SMES is presented. In the viewpoint of the voltage stability, system stabilization criterion of local bus is presented from P­V curve, and then optimal site which can maximize the voltage stabilization of the whole power system, is decided from the proposed voltage stability performance index.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.9-18
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• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.