• 제목/요약/키워드: Optimal Measurement System Placement

검색결과 30건 처리시간 0.043초

전력시스템 고조파 상태 추정에서 면역 알고리즘 적용 (Application of Immune Algorithm for Harmonic State Estimation)

  • 왕용필;박인표;정형환
    • 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.

전력시스템 고조파 상태 춘정에서 GA를 미용한 최적 측정위치 선정 (Optimal Placement of Measurement Using GAs in Harmonic State Estimation of Power System)

  • 정형환;왕용필;박희철;안병철
    • 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).

IA를 이용한 전력시스템 고조파 상태 추정 최적 알고리즘 (An Optimal Algorithm of Harmonic State Estimation using Immune Algorithm on Power System)

  • 박인표;왕용필;정형환;박희철;안병철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 A
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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.

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페이저 측정 시스템의 측정기 최적배치 (Meter Optimal Placement in Measurement System with Phasor Measurement Unit)

  • 김재훈;조기선;김회철;신중린
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 C
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    • pp.1195-1198
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    • 1999
  • This paper presents optimal placement of minimal set of phasor measurement units(PMU's) and observability of measurement system with PMU. By using the incidence matrix symbolic method which directly assigns measurement and pseudo-measurement to incidence matrix, it is much simpler and easier to analyze observability. The optimal PMU set is found through the simulated-annealing(SA) and the direct combinational method. The cooling schedule parameter which is suitable to the property of problem to solve is specified and optimal placement is proven by presented direct combinational method. Search spaces are limited within reasonable feasible solution region to reduce a unnecessary one in the SA implementation based on global search. The proposed method presents to save CPU time and estimate state vectors based on optimal PMU set.

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고조파 상태 추정에 있어서 유전 알고리즘을 이용한 최적 측정위치 선정 (Optimal Placement of Measurements using Genetic Algorithms for Harmonic State Estimation)

  • 정형환;왕용필;이정필;박희철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 A
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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.

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전력시스템 고조파 상태 추정에서 PSO 적용 (Application of Particle Swarm Optimization for Harmonic State Estimation)

  • 왕용필;정종원;김경훈;안병철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 제38회 하계학술대회
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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.

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전력계통의 페이저 측정기 최적배치 (Optimal Placement of the Phasor Measurement Units in Power System)

  • 김재훈;조기선;김회철;신중린
    • 대한전기학회논문지:전력기술부문A
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    • 제49권7호
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    • pp.313-322
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    • 2000
  • This paper presents optimal placement of minimal set of Phasor Measurement Units (PMU's) and observability analysis of the network with PMU's. In order to find a observable system, a symbolic method which directly assigns an appropriate symbol for measurement or pseudo-measurement to every entry of node-branch incidence matrix is proposed. It is much simpler and easier to analyze the observability of the network with PMU's than the conventional ones. For the optimal PMU placement problem, two approaches which are based on a modified Simulated-Annealing (SA) method and a Direct Combination method are proposed. Some case studies with IEEE sample system are made to show the performance of the proposed methods are almost alike and more effective than the conventional simulated-annealing method. It is also shown that the Direct Combination method is more effective than the modified simulated-annealing one in the sense of computation burden. The results of this study showed also that the accuracy of power system estimation and system observability can be improved the proposed PMU placements.

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Optimal Placement of Phasor Measurement Unit for Observation Reliability Enhancement

  • TRAN, Van-Khoi;ZHANG, He-sheng;NGUYEN, Van-Nghia
    • Journal of Electrical Engineering and Technology
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    • 제12권3호
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    • pp.996-1006
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    • 2017
  • Phasor Measurement Unit (PMU) placement is a crucial problem for State Estimation (SE) of the power system, which can ensure that the power network is fully observed. Further, the observation reliability problem of the system has been concerned in the operation conditions. In this paper, based on modified weighted adjacent matrix ($A_w$), an optimal placement method is proposed to solve simultaneously two problems involving the optimal PMU placement problem and the observation reliability enhancement problem of the system. The purpose of the proposed method is to achieve both the minimum total cost and the maximum observation reliability, with a focus on increasing the security of observability, strengthening the observation reliability of buses as well as enhancing the effectiveness of redundancy. Simulations on IEEE 14, 24, 30 and 57 bus test systems are presented to justify the methodology. The results of this study show that the proposed method is not only ensuring the power network having the observability effectively but also enhancing significantly the observation reliability. Therefore, it can be a useful tool for SE of the power system.

전력시스템 고조파 상태추정 지능형 알고리즘 개발 (Intelligent Algorithm of Harmonic State Estimation for Power System)

  • 왕용필;이현정;정형환;김상효;박회철;정동일
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 A
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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).

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A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

  • Arul jeyaraj, K.;Rajasekaran, V.;Nandha kumar, S.K.;Chandrasekaran, K.
    • Journal of Electrical Engineering and Technology
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    • 제10권2호
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    • pp.474-486
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    • 2015
  • This paper proposes a multi-objective optimal placement method of Phasor Measurement Units (PMUs) in large electric transmission systems. It is proposed for minimizing the number of PMUs for complete system observability and maximizing measurement redundancy of the buses, simultaneously. The measurement redundancy of the bus indicates that number of times a bus is able to monitor more than once by PMUs set. A high level of measurement redundancy can maximize the system observability and it is required for a reliable power system state estimation. Therefore, simultaneous optimizations of the two conflicting objectives are performed using a binary coded firefly algorithm. The complete observability of the power system is first prepared and then, single line loss contingency condition is added to the main model. The practical measurement limitation of PMUs is also considered. The efficiency of the proposed method is validated on IEEE 14, 30, 57 and 118 bus test systems and a real and large- scale Polish 2383 bus system. The valuable approach of firefly algorithm is demonstrated in finding the optimal number of PMUs and their locations by comparing its performance with earlier works.