• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.379-389
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• 2014

Low frequency oscillations (LFOs) are load angle oscillations that have a frequency between 0.1-2.0 Hz. Power system stabilizers (PSSs) are very effective controllers in improvement of the damping of LFOs. PSSs are designed by linearized models of the power system. This paper presents a new model of the power system that has the advantages of the Single Machine Infinite Bus (SMIB) system and the multi machine power system. This model is named a single machine normal-bus (SMNB). The equations that describe the proposed model have been linearized and a lead PSS has been designed. Then, particle swarm optimization technique (PSO) is employed to search for optimum PSS parameters. To analysis performance of PSS that has been designed based on the proposed model, a few tests have been implemented. The results show that designed PSS has an excellent capability in enhancing extremely the dynamic stability of power systems and also maintain coordination between PSSs.

• Journal of Advanced Marine Engineering and Technology
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• 제24권2호
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• pp.63-71
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• 2000

This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithm(GA) to improve system stability. Genetic algorithms(GAs) are search algorithms based on the mechanics of natural selection and natural genetics. To verify the validity of the proposed method, investigated damping ratio of the eigenvalues of the electro-mechanical modes system with and without SVC. Also, we considered dynamic response of terminal speed deviation and terminal voltage deviation by applying a power fluctuation at heavy load, normal load and light to verify the robustness of the proposed. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-bus with SVC system.

• 대한전기학회논문지:전력기술부문A
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• 제49권5호
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• pp.212-219
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• 2000

This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithms(GAs) which are search algorithms based on the mechanics of natural of natural selection and natural genetics, to improve system stability. A SVC, one of the Flexible AC Transmission System(FACTS), constructed by a fixed capacitor(FC) and a thyristor controlled reactor(TCR), is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. To verify the robustness of the proposed method, considered dynamic response of generator used deviation and generator terminal voltage by applying a power fluctuation and three-phase fault at heavy load, normal load and light load. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-infinite bus with SVC system.

• 대한전기학회논문지:전력기술부문A
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• 제50권7호
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• pp.324-332
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• 2001

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Static VAR Compensator(SVC) using a Real Variable Elitism Genetic Algorithm(RVEGA). A SVC, one of the Flexible AC Transmission System(FACTS), constructed by a fixed capacitor(FC) and a thyristor controlled reactor(TCR), is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. The proposed PSS parameters are optimized using RVEGA in order to maintain optimal operation of generator under the various operating conditions. To decrease the computational time, real variable string is adopted. To verify the robustness of the proposed method, we considered the dynamic response of generator speed deviation and generator terminal voltage by applying a power fluctuation and three-phase fault at heavy load, normal load and light load. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• 조명전기설비학회논문지
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• 제14권3호
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• pp.49-58
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• 2000

본 논문에서는 FACTS(Flexible AC Transnission System)로 분류되는 여라 기기중 기존의 전압제어 및 무효 전력보상기들이 가지고 있는 바속응성과 불연속성 문제를 해결해줄 수 있는 정지형 무효전력 보상가(Static Var Compensator : SVC)를 포함한 전력계통에 신경회로망 제어기를 적용하여 안정화에 관하여 연구하였다. 제안된 신경회로망 제어기는 오차와 오차변화량을 입력하는 오차역전과 학습 알고리즘을 사용하고, 학습시간올 단축하기 위해 모멘텀 방법을 사용하였다. 제안된 방법의 강인섬을 입증하기 위해 중부하시 및 정상부하시에 초기 전력을 변동시킨 경우와 초기에 회천자각을 변동시킨 경우에 대하여 시스렘의 회전자각, 각속도 편차 특성 및 단 자전압의 동특성을 고찰하여 다른 시스템보다 응답특성이 우수합을 보였다.