• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.900-902
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• 1997

Stabilization of Power systems is investigated using a proportional-integral power system stabilizer(PI PSS). Time division PI PSS is examined in this paper. Two approaches are presented for determining the optimal stabilizer gains of the proposed PI PSS. Simulation results show that the proposed PI PSS yields better system dynamic performance and stability than the sub-optimal stabilizer in the sense of having greater damping in response to a step disturbance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1708-1712
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• 2008

This paper describes a linear matrix inequality (LMI) approach to the design of robust low-order power system stabilizers (PSSs), which are used to damp out local-mode oscillations of synchronous generators. The performance of a PSS is expressed as the location of the closed-loop poles, and a single fixed-gain pole-placement controller is synthesized for a wide range of operating conditions. The synthesis results in simultaneous regional pole-placement stabilization. and is formulated as an LMI feasibility problem with a rank condition. A penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments with a single-machine connected to an infinite bus system were performed to demonstrate the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.177-182
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• 1994

In this paper, an output feedback adaptive variable structure control scheme is presented for stabilization of large scale power systems. An additional input signal which is called a power system stabilizer(PSS) is needed to improve the stability of a power system and to maintain the synchronization of generators. The proposed PSS scheme does not require a priori knowledge of uncertainty bounds. It is guaranteed that the closed-loop system is globally uniformly ultimately bounded by the Lyapunov stability theory. Simulation results for a multimachine power system are given to show the feasibility of the proposed scheme and the superiority of the proposed PSS in comparison with the conventional lead-lag PSS of PID-type.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.60-67
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for a synchronous generator excitation and SVC system. A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the most flexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method. The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.175-181
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• 2009

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 self tuning fuzzy controller for a synchronous generator excitation and SVC system. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.86-88
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• 1995

This paper presents a design technique of the fuzzy PID controller for power system stabilization. PID parameters of the fuzzy PID controller was self-tuned by the fuzzy inference algorithm. The Nosed controller compare with conventional power system stabilizer(PSS) under various of initial value of rotor angle deviation and load condition. The related simulation results show that the Nosed controller was more excellent control characteristics than conventional PSS in transient-state and steady-state response.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.178-187
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• 2007

One important issue in power systems is dynamic instability due to loosing balance relation between electrical generation and a varying load demand that justifies the necessity of stabilization. Moreover, Power System Stabilizer (PSS) must have capability of producing appropriate stabilizing signals over a wide range of operating conditions and disturbances. To overcome these drawbacks, this paper proposes a new method for robust design of PSS by using an auto-tuning fuzzy control in combination with Real-Coded Genetic Algorithm (RCGA). This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs. The RCGA-based method is used for off-line training of this supervisor controller. The proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. By evaluating the simulation results, it is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.506-514
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• 2008

This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.370-374
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• 2015

Various protective equiptments are used for the power system control and protection. Numerous facilities are monitored at the same time in real time and introduction of optimization method and analysis of the method are required for generation control and facility management considering the demand fluctuations. However, the existing system analysis programs are difficult to link with the other sw and there are some problems with user convenience. To solve these problems the present conditions of the system are figured out in real time and the equipment insert method was estimated by optimization method, and the system that showed the system analysis program is developed. PSS/E has been used as system anlysis program for stabilizing system development which applied the optimization. method and Python language is applied in order to link the input and output values with the DB automatically. Lastly, DLL of matlab has been made included in C++ for solving the objective function using opmization method.By linking this to DB, power flow was calculated in PSS/E and the result was represented by Intouch screen.

• 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.