• 대한전기학회논문지:전력기술부문A
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• 제53권12호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.342-344
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• 2002

This paper presents a new strategy to find starting points for placing optimally Phasor Measurement Units(PMUs). The performance of the starting point, initial placement set of PMUs, affect critically the computational burden and/or time, because the Optimal PMU Placement (OPP) problem is formulated the combinatorial optimization. By analyzing the properties of OPP solutions on IEEE sample systems in detail, a new strategy for initial PMU placement, in this paper, is proposed. To verify the performance of the suggested strategy, the comparison with the existing strategy and the new one, on IEEE sample systems. is performed. By using the new strategy, the numbers of search spaces to solve the OPP problem is drastically decreased.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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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).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.378-380
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• 2003

This paper presents the optimal point for measuring harmonic levels in distribution systems. Harmonic should be measure PCC (Point of Common Coupling), where is extended over distribution systems, but some PCCs are limited for economical and technical reason : for this reason, the harmonic measurement for a real distribution system and computer simulation are performed to find the optimal PCC in this paper.

• 한국군사과학기술학회지
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• 제22권2호
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• pp.287-297
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• 2019

Monitoring for the physiological state of a solider is essential to the realization of individual combat system. Despite all efforts over the last decades, there is no report to point out the optimal location of the wearable biosensors considering both monitoring accuracy and operational robustness. In response, we quantitatively measure body temperature and heartrate from 34 body parts using 2 kinds of biosensor arrays, each of which consists of a thermocouple(TC) sensor and either a photoplethysmography(PPG) sensor or an electrocardiography(ECG) sensor. The optimal location is determined by scoring each body part in terms of signal intensity, convenience in use, placement durability, and activity impedance. The measurement leads to finding the optimal location of wearable biosensor arrays. Thumb and chest are identified as best body parts for TC/PPG sensors and TC/ECG sensors, respectively. The findings will contribute to the successful development of individual combat system.