Robust Partial Feedback Linearizing Excitation Controller Design for Higher-Order Synchronous Generator in SMIB Systems to Improve the Transient Stability

A new form of nonlinear control scheme is presented in this brief where the concepts of feedback linearization and adaptive control schemes are combined together to design an adaptive partial feedback linearizing controller. The newly proposed scheme is exercised on a single machine infinite bus (SMIB) power system in order to design its excitation controller in order to eliminate the parameter sensitivity problems of the feedback linearization scheme. The SMIB system is first linearized using the partial feedback linearization technique and the parameters appearing in the feedback linearized model are estimated using the adaptive control scheme. The proposed adaptive partial feedback linearizing excitation controller of the SMIB system uses the estimated values of parameters. The stability of the SMIB system is also analyzed using the Lyapunov stability theory while using the proposed scheme. Simulation studies are carried out to demonstrate the effectiveness of the proposed control scheme over an existing partial feedback linearizing scheme.

Optimal tuning of power system stabilizer (PSS) parameters using genetic algorithm with single objective function is presented in this paper. A Single Machine Infinite Bus (SMIB) system is considered. The main objective of this research paper is to investigate the suitability of genetic algorithm for effective tuning of parameters of the power system stabilizer in a single machine infinite bus system. A conventional speed based lead‐lag PSS is used. A simple and effective method of tuning the parameters of PSS is proposed which is posed as an optimization formulation by maximizing the damping of modes of oscillations of the SMIB system over a wide range of loading conditions and different system configurations. It is found that GA based PSS with single objective design shows improved dynamic performance over Conventional PSS over a wide range of operating conditions and different system parameters.

The problem of transient stability and voltage regulation for a single machine infinite bus (SMIB) system is addressed in this paper. An improved Backstepping design method for transient stability enhancement and voltage regulation of power systems is discussed beginning with the classical Backstepping to designing the nonlinear excitation control of synchronous generator. Then a more refined version of this technique will be suggested incorporating the sliding mode control to enhance voltage regulation and transient stability. The proposed method is based on a standard third-order model of a synchronous generator connected to the grid (SMIB system). It is basically implemented on the excitation side of the synchronous generator and compared to the classical Backstepping controller as well as the conventional controllers which are the automatic voltage regulator and the power system stabiliser. Simulation results prove the effectiveness of the proposed method which ameliorates to a great extent the transient stability compared to the other methods.

This text proposes the design of the integer order IOPID Controller as Power System Stabilizer (PSS) on a SMIB System with AVR excitation and compare the performance by replacing it with fractional order FOPID controller as PSS on the same system. The performance and conduct of the controller adopted are differentiated and evaluated on a Single Machine Infinite Bus (SMIB) system under various distinct loading condition for which Heffron Phillip Model is adopted. The PSS is designed on the basis of its frequency responses by inspecting the system robustness by analyzing sensitivity function, gain margin (GM) and phase margin (PM). This paper first utilizes the IOPID as PSS and then its non-integer form is taken up and designed. It is seen that the performance achieved by using FOPID controller as PSS is better compared to IOPID controller.

This paper proposes an adaptive critic design (ACD) based control method of a generator in a single machine infinite bus (SMIB) power system, by using a biologically-inspired artificial neural network (BIANN). A heuristic dynamic programming (HDP) based optimal controller applying three BIANNs is designed for the control of the turbo generator in the SMIB system. By developing a numerical derivative calculation algorithm, the difficulties in back-propagating errors through a BIANN are overcome. The HDP-BIANN controller for the turbo generator in the SMIB system is trained and run online for different operating conditions. The results show that the HDP-BIANN controller improves the system damping as well as dynamic transient stability more effectively than the conventional controllers (CONVC) for not only small step changes, but also large disturbances such as a three phase short circuit. This is the first time that a BIANN is used for closed-loop optimal control of a power system.

In this paper we present a robust nonlinear excitation controller of synchronous generator connected through one transmission line to an infinite bus (SMIB) to enhance transient stability. Simulation results show that transient stability of a single machine infinite bus power system under a large sudden fault can be improved.

This paper presents an investigation into the optimisation of power system stabiliser (PSS) parameters using multi-power flow conditions. A simple objective function takes into account all the critical operating conditions. The steepest descent optimisation method based on eigen-value sensitivity is used for the minimisation of the objective function. Two types of PSSs are evaluated, namely, the optimised PSS (OPSS) based on multi-power flow conditions and the conventional PSS (CPSS). It is shown that the OPSS performs better than the CPSS on a single machine infinite bus (SMIB) system.

This paper proposes a decoupling based direct method to analyze the post-contingency transient stability for a general multi-machine power system. A linear decoupling transformation is used to construct the same number of independent single machine infinite bus (SMIB) power systems as oscillation modes. Each SMIB system carries stability information regarding one oscillation mode of the original system at the equilibrium. Then, the transient energy function method is applied on all decoupled SMIB systems to calculate stability margins, the smallest of which indicates the stability margin of the original system. Case studies on an IEEE 9-bus power system and a WECC 179-bus power system demonstrate the validity of the proposed method.

This paper studies the control strategies for enhancing the transient stability of a single machine infinite bus (SMIB) power system. First, the dynamical SMIB model is established, and the excitation control is discussed. Next, the damping linear optimal excitation controller (DLOEC) and the output feedback H_infinity control strategy are studied. Then, the DLOEC and the suboptimum H_infinity controller are designed for a specific SMIB power system. The effectiveness of the two presented methods is verified by simulations. The simulation results show that the presented methods improve the transient stability of the SMIB power system and that the H_infinity controller provides better performance than the DLOEC controller.

Steadiness of power system is a significant issue in power system operation. In this article design of Neural Network tuned Fuzzy logic power system stabilizer (NNTFLPSS) for single machine infinite bus (SMIB) system is proposed to settle down low frequency swinging that improves small signal stability in power system. The speed deviance and variation in speed deviance of the rotor of synchronous generator from the trained neural network were considered as the feedback to the fuzzy logic power system stabilizer (FLPSS) to recover the power system from small signal stability problem by refining damping oscillations. The comparative reading was noted for rotor speed deviances and rotor angle deviances using conventional PSS (CPSS), Fuzzy logic based power system stabilizer (FLPSS) and NNTFLPSS. The MATLAB simulation results obtained indicates the improved performance of NNTFLPSS over the CPSS and FLPSS.

Single machine infinite bus (SMIB) power system and multi-machine power system (MMPS) stability improvement by tuning of static var compensator (SVC) based controller parameters are investigated in the proposed method. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and real-coded genetic algorithm is used for searching optimal controller parameters. SMIB power system and MMPS models are developed using MATLAB’s SIMULINK which incorporates SVC controller. A fault is created on the transmission line. The simulation results of SMIB power system and MMPS without SVC controller and with SVC controller are presented. The simulation results are analyzed which show that the power system becomes unstable on the occurrence of the fault if SVC controller is not used. This paper proves the effectiveness of the proposed design. Thus the proposed method enhances the power system stability.

The proposed cascade-type feedback system stabilizes the terminal voltage of single machine infinite bus (SMIB) systems using two measurements: power angle and terminal voltage. The resultant control law only requires the nominal system parameters of the SMIB, and the observer removes any model dependence. This paper provides several contributions. First, the high-order pole-zero cancellation (PZC) technique constructs the observer to estimate the time derivatives of the terminal voltage and power angle measurements without any SMIB model information. Second, the high-order PZC technique enables the outer loop to estimate the desired power angle reference along the critically damped dynamics for the terminal voltage. Third, the observer-based proportional-double integral-derivative control law for the inner loop exponentially stabilizes the power angle error by reducing the closed-loop order to 2 through the high-order PZC technique. A MATLAB/Simulink implementation of the proposed cascade-type feedback system validates the effectiveness of the proposed solution.

Design of Robust Power System Stabilizer using Genetic Algorithm-based Fixed-Structure H∞ Loop Shaping Control

This paper presents an application of control theory to damp out load angle and speed oscillations through the excitation and governor subsystems in a hydro power plant connected as single machine infinite bus (SMIB) system. The control technique used is based on optimal pole shift (PS) theory, unlike linear quadratic regulation (LQR) method, which requires solving an algebraic Riccati equation. The adopted approach offers satisfactory damping on speed and load angle oscillations. The proposed control scheme is demonstrated on light, normal and heavy load operating conditions. It is observed that with the proposed technique, the control design is robust over a wide range of operating conditions. Also in this paper, a comprehensive assessment of the effects of optimal control approach when applied with state-estimation techniques; linear Kalman filter (KF) and first-order divided difference filter (FDDF) has been addressed.

This paper presents a multi-input/multi-output (MIMO) controller for a single machine infinite bus power system using adaptive neural design. Firstly, rather than representing the power system as Hamiltonian system with dissipation, the single machine infinite bus power system is divided into two-sub systems and is transformed into a block-triangular form. Secondly, we design for each subsystem an adaptive neural controller. Semiglobal uniform ultimate boundedness of all the signals in the closed-loop of the single machine infinite bus power system is guaranteed. The outputs of the system are proven to converge to a small neighborhood of the desired trajectories. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.