• Journal of Electrical Engineering and Technology
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• v.9 no.2
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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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• v.24 no.2
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.5
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.7
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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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.49-58
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• 2000

This paper deals with a systematic approach to neural network controller design for static VAR compensator (SVC) using a learning algorithm of error back propagation that accepts error and change of error as inputs, the momentum learning technique is used for reduction of learning time, 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, we considered the dynamic response of generator rotor angle deviation, angular velocity deviation and generator terminal voltage by applying a power fluctuation and rotor angle fluctuation in initial point when heavy load and normal load. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.