• 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.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.495-497
• /
• 2005

A new small signal stability analysis method for eigenvalue analysis is presented. This method is called RCF method and based on the computation of the state transition equations and state transition matrix over a specified time interval that corresponds to one or some cycle operations of the system. This method is applicable to any system with or without switching elements. As an applicable example of RCF method in power system, the one machine infinite bus system connected switching SVC at generator terminal is investigated and the results proved that variations of oscillation modes after switching operations can be calculated exactly.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.288-295
• /
• 2005

In this paper a new adaptive, decentralized excitation control scheme proposed to enhance the transient stability of multimachine power systems is extensively analyzed with respect to its robustness and disturbance attenuation. As shown in the paper, both robustness and disturbance attenuation can be effectively improved by suitably selecting the design parameters of the proposed controller. Particularly, some simple rules for the selection of the control gains and the adaptation parameters are extracted which, as it is proven, may be essential for the system performance. Simulation tests on a two generator infinite bus power system absolutely confirm the theoretical results.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.302-307
• /
• 2005

A novel neuro controller based simple neuro-structure with modified error function is introduced in this paper. This controller consists of two independent controllers, known as the voltage regulator and the angular controller. The voltage regulator is used to modify terminal voltage for the purpose of tracking a reference voltage. The angular controller is utilized to guarantee the stability of the system. In this structure each neuron uses a linear hard limit activation function that depends on the controlled variable and its derivatives. There is no need for parameter identification or any off-line training data. Two proposed controllers are merged by a smooth switch to build a complete controller. The effectiveness of the proposed novel control action is demonstrated through some computer simulations on a Single-Machine Infinite-Bus (SMIB) power system.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.262-269
• /
• 2005

In this paper, a nonlinear robust control approach is applied to design a controller for the Static Synchronous Compensator (STATCOM). A robust control dynamic model of STATCOM in a one-machine, infinite-bus system is established with consideration of the torque disturbance acting on the rotating shaft of the generator set and the disturbance to the output voltage of STATCOM. A novel recursive approach is utilized to construct the energy storage function of the system such that the solution to the disturbance attenuation control problem is acquired, which avoids the difficulty involved in solving the Hamilton-Jacobi-Issacs (HJI) inequality. Sequentially, the nonlinear disturbance attenuation control strategy of STATCOM is obtained. Simulation results demonstrate that STATCOM with the proposed controller can more effectively improve the voltage stability, damp the oscillation, and enhance the transient stability of power systems compared to the conventional PI+PSS controller.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.278-287
• /
• 2005

In this paper a new excitation control scheme that improves the transient stability of multi machine power systems is proposed. To this end the backstepping technique is used to transform the system to a suitable partially linear form. On this system, a combination of both feedback linearization and adaptive control techniques are used to confront the nonlinearities. As shown in the paper, the resulting nonlinear control law ensures the uniform boundedness of all the state and estimated variables. Furthermore, it is proven that all the error variables are uniformly ultimately bounded (DUB) i.e. they converge to arbitrarily selected small regions around zero in finite-time. Simulation tests on a two generator infinite bus power system demonstrate the effectiveness of the proposed control.

• Proceedings of the KIEE Conference
• /
• 2002.07a
• /
• pp.59-62
• /
• 2002

Before a developed digital Power System Stabilizer(PSS) is installed to real power system, an efficient trial test for installing PSS is needed. In this paper, the performance of developed digital PSS for a single hydro-turbine generator and infinite bus system has been investigated using Real Time Digital Simulator(RTDS) in order to install PSS to real power system practically. The test system was composed of RTDS, three phase voltage/current amplifier and the PSS and the test scheme provided a very efficient way to verify the design and control performance of a PSS to be applied to real power system. The trial installation test through AVR 3% step test and three fault analysis may be guaranteed to install PSS to real power system.

• Proceedings of the KIEE Conference
• /
• 2000.11a
• /
• pp.187-189
• /
• 2000

In this paper, QFT robust control strategy is proposed to improve stability of power systems in the presence of parametric uncertainty. The basic idea in QFT is to convert design specifications of a closed loop system and plant uncertainties into robust stability and performance bounds on the open loop transmission of the nominal system and then to design a controller by using the gain-phase loop sharing technique. The robustness of the QFT controller has been investigated on a single machine infinite bus model by nonlinear simulations.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2188-2190
• /
• 2004

This paper presents an implementation of power system stabilizer using inverse dynamic neuro controller. Traditionally, mutilayer neural network is used for a universal approximator and applied to a system as a neuro-controller. In this case, at least two neural networks are used and continuous tuning of neuro-controller is required. Moreover, training of neural network is required considering all possible disturbances, which is impractical in real situation. In this paper, Taylor Model Based Inverse Dynamic Neuro Model (TMBIDNM) is introduced to avoid this problem. Inverse Dynamic Neuro Controller (IDNC) consists of TMBIDNM and Error Reduction Neuro Model (ERNM). Once the TMBIDNM is trained, it does not require retuning for cases with other types of disturbances. The controller is tested for one machine and infinite-bus power system for various operating conditions.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.157-160
• /
• 1992

An approximate method for the dominant eigenvalue of one machine connected to the infinite bus has been suggested. This method is based on combining the traditional eigenvalue sensitivity analysis and the structure of the system state matrix. Numerical examples are presented. This method is considered to be quite useful in the stability analysis for various initial conditions and for adjustment of generator controller parameters.