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

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.84-86
• /
• 2005

Adaptive tracking, disturbance rejection and power system stabilizer. First, this paper deals with power system stabilization problem using asymptotic tracking of arbitrary smooth bounded reference output signals, with simultaneous rejection of disturbances generated by an unknown linear exosystem. Second, this paper presents a power system stabilizer(PSS) using nonlinear adaptive observer backstepping controller.

• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1060-1062
• /
• 1999

This paper proposes a guideline of choosing the optimum stabilizer input considering the gain margin of power system stabilizer between the optimum stabilizer gain and the allowable maximum stabilizer gain in accordance with the five inputs, such as generator shaft speed, bus frequency, electrical power, accelerating power and bus terminal voltage. The local mode damping and exciter mode damping are considered with increasing the stabilizer gain to determine each gain margin of the inputs.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.281-286
• /
• 2005

The main objective of the research work presented in this article is to present a systematic approach for designing a multilayer feed-forward artificial neural network based self-tuning power system stabilizer (ST-ANNPSS). In order to suggest an approach for selecting the number of neurons in the hidden layer, the dynamic performance of the system with ST-ANNPSS is studied and hence compared with that of conventional PSS. Finally the effect of variation of loading condition and equivalent reactance, Xe is investigated on dynamic performance of the system with ST-ANNPSS. Investigations reveal that ANN with one hidden layer comprising nine neurons is adequate and sufficient for ST-ANNPSS. Studies show that the dynamic performance of STANNPSS is quite superior to that of conventional PSS for the loading condition different from the nominal. Also it is revealed that the performance of ST-ANNPSS is quite robust to a wide variation in loading condition.

• Journal of Electrical Engineering and information Science
• /
• v.2 no.3
• /
• pp.88-94
• /
• 1997

This paper presents the sliding mode observer-model following (SMO-MF) power system stabilizer(PSS) for unmeasurable state variables. This SMO-MF PSS is obtained by combining the sliding mode-model following (SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). The control input of the proposed MO-MF PSS is derived by Lyapunov's second method to determine a control input that keeps the system stable for unmeasurable plant state variables. Simulation results show that the proposed SMO-MF PSS including CLF is able to reduce the low frequency oscillation and to achieve asymptotic tracking error between the reference mode state and the estimated plant state at different initial conditions.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.12
• /
• pp.611-623
• /
• 2002

This paper introduce the real time digital simulator which is located in Korea Electric Power Research Institute. This paper also describes the methodology for the performance test of the PSS using KEPS. This test is to get a high degree of the confidence of the developed PSS before it is installed into the real power system. This has been performed in the form of closed-loop tests in which Simulator and PSS are connected and signals come and back interactively. Many tests have successfully done using KEPS which consists of 26 RTDS racks, under the large-scale power system. The simulated reduced KEPCO power system contains 88 generators and 295 buses. Through the AVR step, three phase fault and active power variation test, the effectiveness of developed PSS has been proved. This paper also presents the overview of KEPS and hardware of protype PSS.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.3
• /
• pp.402-410
• /
• 2013

In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.52 no.1
• /
• pp.1-8
• /
• 2003

This paper presents a novel application method of H$_{\infty}$ optimization method to the design of Power System Stabilizer(PSS) and experimental results through hardware simulator. The approach is focused on decision of performance index and selection strategy of weighting functions together with its tuning for direct design. As the Purpose of the PSS is to increase system damping at very narrow frequency band, weighting functions are determined differently from the case of general servo system control. The designed PSS was confirmed through experiments on a hardware simulator.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.229-231
• /
• 2005

This paper presents the nonlinear $H_{\infty}$ switching power system stabilizer (PSS) based on Lie group and Lie transformation theory. The proposed controller combines the $H_{\infty}$ switching controller and Lie theory. The proposed power system stabilizer (PSS) is used to improve the transient stability in the time-domain and to solve the problem associated with the inaccessible state variables by measuring only the angular velocity. In the simulation study, the different load conditions, fault periods, and fault locations are considered. The nonlinear time-domain simulation showed that the proposed controller was effective restoring transient stability in a one-machine infinite-bus power system.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.12
• /
• pp.655-660
• /
• 2004

This paper deals with the design of a fixed-structure $H_\infty$ power system stabilizer (PSS) by using an iterative linear matrix inequality (LMI) method. The fixed-structure $H_\infty$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the practical applicability of the proposed algorithm.