• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.117-120
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• 2002

Electrical power system has very complexity problem that it is plan measurement system to achieve Harmonic State Estimation (HSE). This complexity problem depends on discord of necessary accuracy, certainty of noise that exist in data communication damage and converter, adaptability of network modification and minimum of expense size of system, estimated monitering. Also, quantity of available measurement equipment for harmonic measurement has been limited. Therefore, systematic method that choose measurement location for harmonic state estimation. This paper is that see proposed HSE that use Observability Analysis(OA) for harmonic state estimation of electrical power system. OA depends on measurement number, measurement location and measurement form here, it is analysis method that depend on network form and admittance of the system. OA used achieve harmonic state estimation that it is Applied to New Zealand electrical power system to prove validity of HSE algorithm that propose. This study result about harmonic state estimation of electrical power system displayed very economical and effective method by OA.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.26-28
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• 2001

This paper discussed for harmonic analysis of 154kv system in Kwangyang steel works. The harmonic modelings are developed by harmonic measurement for scores of days in a 154kv substation at a same time. In this paper, the measurement values of harmonic are compared to the analysis results in incoming line. Case studies are presented to predict harmonic distortion of the future system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.645-654
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• 2004

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using Immune Algorithm (IAs). This IA-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using Immune Algorithm (IAs) in the HSE.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.259-261
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• 2002

Recently, according to the spread of semiconductor applied technology like motor speed control contrivance, power conversion installation and so on, harmonic ingredients occurred in switching operation flow into a distribution system and increase voltage distortion of distribution system and bring on obstacles like damage, lowering of capability, false operation and so on of various electrical installation. So, in order to consider a countermeasure to limit occurrence quantity of harmonic source, harmonic interception and others, precision measurement and analysis on voltage, current, power, power factor, the each ingredient of harmonic order, the percentage of total harmonic distortion and so forth are needed. In this paper monitoring system to measure and analyze power quality connected with power harmonics was developed and it's performance is verified by measuring and analyzing three-phase voltage and current of R, S, T in the three-phase and four-wire system using the developed measurement system.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1163-1175
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• 2016

In recent years, microgrids have been the focus of considerable attention in distributed energy distribution. Microgrids contain a large number of power electronic devices that can potentially cause negative impedance instability. Harmonic impedance is an important tool to analyze stability and power quality of microgrids. Harmonic impedance can also be used in harmonic source localization. Precise measurement of microgrid impedance and analysis of system stability with impedances are essential to increase stability. In this study, we introduce a new square wave current injection method for impedance measurement and stability analysis. First, three stability criteria based on impedance parameters are presented. Then, we present a new impedance measurement method for microgrids based on square wave current injection. By injecting an unbalanced line-to-line current between two lines of the AC system, the method determines all impedance information in the traditional synchronous reference frame d-q model. Finally, the microgrid impedances of each part and the overall microgrid are calculated to verify the measurement results. In the experiments, a simulation model of a three-phase AC microgrid is developed using PSCAD, and the AC system harmonic impedance measuring device is developed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.149-150
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• 2006

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Intelligent Algorithms (IAs). This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Intelligent Algorithms (IAs) in the Harmonic State Estimation(HSE).

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.298-300
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• 2002

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. In particular, the number of available harmonic instruments(Continuous Harmonic Analysis in Real Time : CHART) is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs). This HSE has been applied to the New Zealand AC Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using GAs in the HSE.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.92-94
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• 2003

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic instruments (Continuous Harmonic Analysis in Real Time : CHART) is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using Immune Algorithm (IAs). This HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using IAs in the HSE.

• Proceedings of the KIEE Conference
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• summer
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• pp.286-288
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• 2004

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs). This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).