• 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.

• 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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• 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).

• 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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• 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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• 2007.07a
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• pp.529-530
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• 2007

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 PSO. This PSO-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 PSO in the HSE.