P.K. Dash

S-transform-based intelligent system for classification of power quality disturbance signals

In this paper, a new approach is presented for the detection and classification of nonstationary signals in power networks by combining the S-transform and neural networks. The S-transform provides frequency-dependent resolution that simultaneously localizes the real and imaginary spectra. The S-transform is similar to the wavelet transform but with a phase correction. This property is used to obtain useful features of the nonstationary signals that make the pattern recognition much simpler in comparison to the wavelet multiresolution analysis. Two neural network configurations are trained with features from the S-transform for recognizing the waveform class. The classification accuracy for a variety of power network disturbance signals for both types of neural networks is shown and is found to be a significant improvement over multiresolution wavelet analysis with multiple neural networks.

Application of a multivariable feedback linearization scheme for STATCOM control

This paper investigates application of a multivariable control technique to the multi-input multi-output (MIMO) nonlinear model of a static synchronous compensator (STATCOM). The proposed controller design is based on a feedback linearization scheme. Its prime goal is the coordinated control of ac and dc voltage for a STATCOM installed in a power distribution system. First, the nonlinear mathematical model of STATCOM along with the distribution system is derived. Then, by using input–output feedback linearization, a state feedback control law is obtained by pole placement. The efficacy of the control strategy is evaluated by digital computer simulations on the complete system for various types of loads and/or disturbances. The comparative study of these results with those obtained in a conventional cascade control architecture establishes the elegance of this new control scheme.

A fuzzy variable structure controller for STATCOM

Abstract Two new variable structure fuzzy control algorithms are presented in this paper for controlling the reactive component of the STATCOM current in a power system. The control signal is obtained from a combination of generator speed deviation and STATCOM bus voltage deviation fed to the variable structure fuzzy controller. The parameters of these fuzzy controllers can be varied widely by a suitable choice of membership functions and parameters in the rule base. Simulation results for typical single-machine and multimachine power systems subject to a wide range of operating condition changes confirm the efficiency of the new controllers.

Design of a nonlinear variable-gain fuzzy controller for FACTS devices

The paper presents the design of a nonlinear variable-gain fuzzy controller for a flexible ac transmission systems (FACTS) device like the unified power flow controller (UPFC) to enhance the transient stability performance of power systems. The fuzzy controller uses a numerical consequent rule base of the Takagi-Sugeno type, which can be either linear- or nonlinear-producing control-gain variation over a very wide range. This type of fuzzy control is expected to be more robust and effective in damping electromechanical oscillations of the power systems in comparison with the conventional PI regulators used for UPFC control. Computer simulation results validate the superior performance of this controller.

Multivariable nonlinear control of STATCOM for synchronous generator stabilization

A static synchronous compensator (STATCOM) is a typical flexible ac transmission system device playing a vital role as a stability aid for small and large transient disturbances in an interconnected power system. This article deals with design and evaluation of a feedback linearizing nonlinear controller for STATCOM installed in a single-machine infinite-bus power system. In addition to the coordinated control of ac and dc bus voltages, the proposed controller also provides good damping to the electromechanical oscillation of the synchronous generator under transient disturbances. The efficiency of the control strategy is evaluated by computer simulation studies. The comparative study of these results with the conventional cascade control structure establishes the elegance of the proposed control scheme.

A fuzzy variable structure current controller for flexible AC transmission systems

The paper presents the design of function based variable structure fuzzy controllers for flexible AC transmission systems to improve transient stability performance. This controller is tested on a very widely considered FACTS device like static compensator (STATCOM) which is simulated by a current injection model comprising both real and reactive components. The function based fuzzy controller uses the Takagi-Sugeno scheme and generates the proportional action which by one-to-one or one-to-two mapping can produce the variable gain PI controller. Unlike the performance based two input fuzzy controllers considered earlier, the function based one input fuzzy controller dispenses with gain dependency and provides independent tuning for proportional and integral gains. This new fuzzy controller is tested on a single-machine infinite-bus power system operating with a STATCOM for a variety of transient disturbances and variation of operating point to validate its superior performance in comparison to the conventional PI controllers.

A feedback linearization based fuzzy-neuro controller for current source inverter-based STATCOM

This paper presents a nonlinear control approach to the MIMO system of a current source inverter (CSI) based static synchronous compensator (STATCOM). Nonlinear control approach based on feedback linearizing scheme for FACTS devices has been proved in previous literature to have superior performance In damping the electromechanical oscillations of the power system. In this proposed control scheme, the artificial neural network (ANN) will be trained based on feedback linearization control scheme. Radial basis function neural networks (RBFNN) are used as online approximators to learn the unknown dynamics of the system. However, steady state error after the disturbances occurs in conventional feedback linearizing controller. Thus, training of RBFNN as conventional feedback linearizing controller became unrealizable. Consequently, fuzzy controller based on TSK IV control scheme has been used to filtered out the steady state error. This proposed controller is expected to approximate and replace complex mathematical equations of feedback linearization control scheme. To demonstrate the application of the proposed controller, case studies are done with a single-machine infinite-bus power system with current source inverter (CSI)-based STATCOM installed at certain bus. The efficacy of the control strategy is evaluated by digital computer simulation studies using MATLAB under various transient disturbances and a wide range of operating conditions. The approximated control signals are compared with that of targeted control signals to exhibit the elegance of the proposed control scheme.

A fuzzy-feedback linearizing nonlinear control of CSI based STATCOM for synchronous generator stabilization

This work presents a nonlinear control approach to the MIMO system of a current source inverter (CSI) based static synchronous compensator. Here, a nonlinear mathematical model of transmission STATCOM is derived. Then, by input-output feedback linearization, a state feedback control law is obtained by pole placement. The proposed controller provides good transient stability for synchronous generator under transient disturbances. Besides, fuzzy controller is implemented together with feedback linearizing controller to improve the performance. The efficacy of the control strategy is evaluated by digital computer simulation studies. The comparative study of these results with conventional controller establishes the elegance of the proposed control scheme.