• 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.60 no.4
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• pp.711-716
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• 2011

This paper defines a generator reactive reserve considering power system network. Conventional generator reserve is calculated by the difference between the maximum reactive power output of generator and the current reactive power of generator. However, all generators could not affect on the whole power system. Thus, the effective generators should be selected by sensitivity analysis. The sensitivity depends on network configuration is the relation between generator reactive power outputs and reactive power loads. Using the sensitivity, the effective generator reactive reserve can be calculated.

• 전기의세계
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• v.26 no.1
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• pp.63-70
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• 1977

This paper deals with computer analysis technique of the network having 3-terminal elements whose input and output characteristics are defined by nonuniform spacing function group on the volt-ampere space. Developing the algorithms to obtain the solutions of the network mentioned above by computer, we propose optimization technique, which can solve the normal form equations of the network defined in this paper and which involves mode analysis technique to be able to analyze the case that the function group has negative resistance characteristics.

• ETRI Journal
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• v.42 no.5
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1913-1918
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• 2016

In order to analyze the power consumption pattern of the DC urban rail system, the method to obtain a solution establishing the current equation according to fixed position of the substation and varying position of the train is used. The proposed analysis method using the network analysis is to model the transfer function of the component constituting a direct current power supply system (dc substation, train, catenary) to the voltage and current. By multiplying the model formula consecutive, it can calculate the voltage and current of each element of power supply circuit and shows a simple case analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.923-931
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• 2017

A power grid is one of the most complex networks and is critical infrastructure for society. To understand the characteristics of a power grid, complex network analysis has been used from the early 2000s mainly for US and European power grids. However, since the power grids of different countries might have different structures, the Korean power grid needs to be examined through complex network analysis. This paper performs the analysis for the Korean power grid, especially for high-voltage transmission networks. In addition, statistical and small-world characteristics for the Korean power grid are analyzed. Generally, the Korean power grid has similar characteristics to other power grids, but some characteristics differ because the Korean power grid is concentrated in the capital area.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.882-887
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• 2014

In this paper, the water cooling method among the forced coolant cooling methods is considered to be applied to the 110kW-class IPMSM for railway vehicles. First, basic thermal property analysis of the IPMSM is conducted using the three-dimensional thermal equivalent network method. Then, based on the results of the basic thermal property analysis, some design requirements for the water cooling jacket are deduced and a basic design of the water cooling jacket is carried out. Finally, thermal equivalent circuit of the water cooling jacket is attached to the IPMSM's 3D thermal equivalent network and then, the basic thermal and effectiveness analysis are conducted for the case of applying the water cooling jacket to the IPMSM. In the future, the thermal variation trends inside the IPMSM by the application of the water cooling jacket is expected to be quickly and easily predicted even at the design step of the railway traction motor.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.55-58
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• 1995

An optimum design method of electric machines using neural network is presented. In this method, two multi - layer perceptrons of analysis and design neural network are used in optimizing process. A preliminary model of linear induction motor for subway is designed by the electric and magnetic loading distribution method and then optimized by presented method.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.791-793
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• 2000

The fuzzy inference system is a popular computing framework based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. The advantage of fuzzy approach over traditional ones lies on the fact that fuzzy system does not require a detail mathematical description of the system while modeling. As modeling method. the Group Method of Data Handling(GMDH) is introduced by A.G. Ivakhnenko GMDH is an analysis technique for identifying nonlinear relationships between system's inputs and output. We study a Novel Neuro-Fuzzy Network (NNFN) in this paper. NNFN is a network resulting from the combination of a fuzzy inference system and polynomial neural network(PNN) (7) which is advanced structure of GMDH. Simulation involve a series of synthetic as well as experimental data used across various neurofuzzy systems.