• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.12-14
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• 2007

A voltage transformer (VT) is used to transform a high voltage into a low voltage as an input for a metering device or a protection relay. VTs use an iron core which maximizes the flux linkage. The primary current of the VT has non-fundamental components caused by the hysteresis characteristics of the iron core. It causes a voltage drop in the winding impedances resulting in the error of the VT. This paper describes a compensation algorithm for the VT. The proposed algorithm can compensate the secondary voltage of VT by calculating the primary current from the exciting current of the hysteresis loop in the voltage transformer. In this paper, the exciting branch was divided into a non-linear core loss resistor and a non-linear magnetizing inductor. The performance of the proposed algorithm was validated under various conditions using EMTP generated data. Test results show that the proposed compensation algorithm can improve the accuracy of the VT significantly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1457-1462
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• 2009

This paper proposes a compensating algorithm for the secondary voltage of a coupling capacitor voltage transformer (CCVT) in the time domain by considering the hysteresis characteristics of the core. The proposed algorithm estimates the three error terms i.e. the voltage across the secondary winding parameters, the voltage across the primary winding parameters, and the voltage across the capacitor and the tuning reactor. These three terms are added to the measured secondary voltage to obtain the correct voltage. The algorithm reduces the errors of the CCVT significantly both in the steady state and during a fault. The performance of the algorithm is verified under the various fault conditions by varying the fault distance, the fault inception angle, and the fault impedance with the EMTP generated data. Test results clearly indicate that the algorithm can increase the accuracy of a CCVT significantly under the fault conditions as well as in the steady state. The algorithm helps improve the performance of a protection relay or a metering device.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.241-255
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• 2012

Recently, smart home environments which provide complex services through smart appliances are becoming realized, due to the advances in connected devices and network technologies. Current smart home environments are mostly restricted, because of difficultly of integration of heterogeneous smart appliances. Therefore radical service integration is impracticable. In this paper, we analyze and implement Machine-to-Machine (M2M) standards which are established by European Telecommunications Standards Institute (ETSI) for integrating heterogeneous devices and services. Smart Home is one of the areas covered by ETSI M2M standards, however these standards are just standardized, so adaption and assessment in smart home are not proved yet. Therefore, this paper analyze ETSI M2M standards by focusing the data transport model and evaluate by selecting the most commonly used smart home scenarios and by implementing ETSI M2M standards compatible smart metering system. In some points ETSI M2M standards are not efficient because of its complexity of structure, however ETSI M2M provides sophisticated features for integrating M2M which are appropriate to adopt diverse smart home environments.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.281-292
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• 2011

In this paper, a simulator adapted in AMI network environment with NS-2 was designed and implemented. The limited AMI operation environment such as processing times of data, network protocol and system performance can be simulated to find out the optimal AMI formations. Consequently, it is simulated under conditions that are closely analogous to the actual networks and each device. In future, the result of simulation would be applied to AMI network, mitigated the waste of resources and much contributed towards the real optimal AMI deployments in utilities.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.3
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• pp.141-146
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• 2016

The AMR(automatic meter reading) system has been increasingly and widely used for its efficient and intelligent management, which is a technology that automatically collects consumption data from a water meter or energy metering device. The digital meter instead of the mechanical meter should be used in the system. Up to now, various types of sensor to measure the water flow rate have been used in the digital water meter, for example, reed switch, photo IR approximate sensor, ultrasonic sensor, electromagnetic sensor, etc. In this paper, a new sensing technology, where a variable capacitor and digital circuit were used for sensing the water flow rate, was proposed. The circuit was designed and verified by Pspice simulation. And a PCB board for the circuit was fabricated. After then, a prototype of digital water meter using a variable capacitor to measure the water flow rate was fabricated. The function tests of the fabricated digital water meter were performed, and it was found that the meter worked properly. Since the new technology has much better properties in terms of cost and power consumption compared to conventional technologies, it should be one of the major digital water meter technologies in the future.

• KIEE International Transactions on Power Engineering
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• v.4A no.4
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• pp.214-220
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• 2004

Power quality monitoring is the cornerstone for power quality analysis, diagnosis and improvement. The measurement of power quality (PQ) evolves from instantaneous metering to continuous monitoring. Furthermore, recent technologies enable us to construct more flexible, reliable, rapid and economical power quality monitoring system (PQMS). Therefore, this paper presents an improved PQMS with a new distributed monitoring structure. The proposed PQMS consists of a PQ meter, PQ analyzer and GUI. The PQ meter only collects raw data and the PQ analyzer performs power quality analysis. It has several advantages compared to conventional structures in economic efficiency, modularity, speed, etc. PQ monitoring algorithms to catch steady-state trends and to detect PQ events are also adapted to the proposed structure. Using the proposed structure and monitoring algorithm, a prototype PQMS is constructed and real-time testing is performed.

• Journal of Multimedia Information System
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• v.1 no.2
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• pp.111-118
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• 2014

The Smart grid refers to the technology that enables efficient usage of electric power by collecting information concerning the power usage and power lines grafting information and communications technology to onto power grids. There are Zigbee, PLC or IEEE 802.11 WLAN MAC as a core technology of the Smart grid, but in this paper, the discussion is focused on the PLC. The PLC is the technology that carries out data communications using power lines and put into practical use in the field of lights or home appliances control recently but PLC-applied communications between electronic devices are rarely seen. For the reason that the PLC uses high-voltage power lines and has a disadvantage of experiencing higher data loss rate caused by the noises produced by going through transformers, the technology is yet to be used in many areas. Nevertheless, the PLC has been studied widely recently in respect that it's the low-cost communication solution for the Smart Metering [1]. Moreover, this technology is emerging as a novel data communication method and discussed as an important technology lately due to the developments of the Smart grid systems and Internet of things (IoT). Thus, in this paper, the results obtained from designing and performing implementation scenario for the PLC-based Smart grid home network system were compared and analyzed with that of IEEE 802.11 WLAN MAC (the foundation technology at Jeju Smart grid Test bed)-based Smart grid home network. Thus, in this paper, OPNET 14.5 PL8, OSI 7 layer, PLC router nodes and PLC nodes had been used for the designing and implementation simulations of both systems. Additionally, QoS was not considered in order to guarantee that all the traffics would not have the same processing priority.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.712-719
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• 2013

This paper studies the security module for the reliable transmission of the meter reading and the control data between the remote terminals and the upper server-side in smart water grid. The proposed security module was implemented to make it attachable to the remote terminal without security function. In particular, unlike the smart grid of electric field, the low power is considered due to the use of battery power in the smart water grid, and the ARIA-GCM-128 symmetric key method is adopted taking into the account that the damp and constrictive environments by the installed meter location in the underground occur a communication obstacle on building of the large-scale network system. The encryption module of this paper was devised to ensure the safety between the reading data on the terminal and the control data from the upper server, and secure the stability of the remote meter reading system by taking protection against an arbitrary alteration or modification.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1799-1807
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• 2016

In this paper, we propose the automatic demand response systems which reduce the electric power consumption for the period automatically distinct from the existing passive demand response that a subscriber directly controls the energy consumption. The proposed systems are based on SEP 2.0 and consist of the demand response management program, the demand response server, and the demand response client. The demand response program shows the current status of the electric power use to a subscriber and supports the function which the administrator enables to creates or cancels a demand response event. The demand response server transmits the demand response event received from the demand response management program to the demand response client through SEP 2.0 protocol, and it stores the metering data from the demand response client in a database. After extracting the data, such as the demand response the start time, the duration, the reduction level, the demand response client reduces the electric power consumption for the period.