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

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.

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.

Growth in power demand without increased network expansion necessitates that the stability of the power system with minimum of control systems is required to stay within the reference point of safe and reliable operation of the grid. In this paper, a three-machine nine-bus power system with a wind park is used for stability analysis and a H 2 /H ∞ robust power system stabilizer (PSS) is designed for damping oscillations. System performances after various disturbances are discussed by comparing the proposed PSS with conventional PSS. The results show that the robust PSS has stronger robustness and it is more reliable than conventional PSS (CPSS) under various disturbances.

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.

Low-frequency oscillations in power systems sometimes lead to larger disturbances leading to instability. Addition of power system stabilizer (PSS) is very effective in damping the oscillations. The main purpose of the PSS is to increase damping of synchronous machines in the excitation loop. In this paper a new meta-heuristic algorithm termed Quasi-oppositional symbiotic organism (QOSS) search has been proposed for designing the PSS parameters in an optimal manner. The technique is tested on both single machine infinite bus system as well as a multi-machine system. Various operating conditions like loading effect and line outages are also considered for establishing robustness of PSS. The PSS parameters are tuned with the help of other optimizations like Symbiotic organism search, Genetic algorithm and Particle swarm optimization and are compared with those obtained with the application of QOSOS, to show the superiority of the proposed algorithm.

This research evaluates the viability of the artificial eco-system optimization (AEO), a novel metaheuristic algorithm, for optimal power system stabilizers (PSSs) tuning in single-machine infinite bus (SMIB) and western system coordinating council (WSCC) multi-machine power systems. The PSS design problem was converted to an optimization problem to achieve optimal tuning, and an eigenvalue-based objective function was employed. The eigenvalue objective function was defined to optimally obtain the PSSs parameters and enhance the power system dynamic performance by improving the damping of electromechanical modes (EMs). The proposed AEO-based PSS performance was validated by comparing the results obtained with genetic algorithm (GA)-based PSS, particle swarm optimization (PSO)- based PSS design, and similar published work. AEO-based PSS method of tuning has been shown to damp electromechanical modes (EMs), control low-frequency oscillations (LFO), and provide better transient performance and convergence rate. Cite this article as: T. Ebuka Odoh, A. Sabo, N. Izzri Abdul Wahab and H. Beiranvand, "Artificial eco-system-based optimization algorithm for optimal design of single-machine infinite bus power system stabilizer," Electrica, 23(3), 522-533, 2023.

In this paper, a robust partial feedback linearizing excitation controller is designed for synchronous generators to enhance the transient stability of single machine infinite bus (SMIB) power systems. The seventh-order dynamical model of synchronous generators including dynamic characteristics of IEEE Type-II exciters are taken into consideration to design this robust excitation controller. Uncertainties associated with both parameters and states are taken into account during the controller design while bounding these uncertainties such that matching conditions are satisfied. In addition, measurement noises are incorporated within the system model which are decoupled through the proposed control scheme and the robustness is ensured through against these noises. The partial feedback linearization method is employed to transform the nonlinear dynamical model into a partially linear system which is then used to design the auxiliary excitation control input for the synchronous generator in an SMIB system. The performance of the proposed excitation control scheme is analyzed on an SMIB system following large disturbances including a comparative study with a conventional power system stabilizer (PSS).

In this paper, low frequency oscillations in power system under the different operating conditions have been solved through PID based power system stabilizer. The tuning of the parameters of the PSS are considered as optimization problem, and the parameters are tuned using genetic search algorithm. Here forth-order linear and non-linear model of the synchronous machine (model 1.1) which includes both the generator main field winding and the damper winding in q-axis is considered for finding out the sensitivity of electromechanical modes of single machine infinite bus system. The effectiveness of automatic voltage controller, and PID-power system stabilizer are identified through eigen value analysis and participation factor method. The non-linear simulation results show the effectiveness and capability of PID-PSS for power system stability improvement under various disturbances.

In this paper, we propose a new technique used to design a robust controller that is not as high-order and complicated as the ones designed by conventional \(\cal{H}\) ∞ loop shaping method. The proposed algorithm is called Genetic Algorithm (GA) based fixed-structure H ∞ loop shaping control. In the approach, GA is adopted to solve the H ∞ loop shaping design problem under a structure specified controller. The performance and robustness of the proposed controller are investigated in a buck-boost converter in comparison with the controllers designed by conventional H ∞ loop shaping and conventional ISE method. Results of simulations demonstrate the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances. Experiments are performed to verify the effectiveness of the proposed technique.Keywords H ∞ loop shapingRobust controllerGenetic algorithmBuck-boost converter

The main purpose of engineers is to increase the capacity of transferred power in the power system. Power system getting pretentious by momentary change in voltage and current that creates swings and instability in the synchronous machine. Here paper represents formulation and simulation of single machine infinite bus system (SMIB) and also deals with four area ten bus system which contains four generators. Power system stabilizers are connected to excitation systems for improving the damping during low frequency fluctuations. Power system stabilizer will create an additional signal which is supplied to excitation system so that it will damp out the fluctuations. In order to improve stability, the performance of the proposed HS-PSS controller, a time domain performance criterion function was also defined compared with genetic algorithm (GA), the proposed method was indeed more efficient and robust in improving stability of power system network.

This paper presents an adaptive method to design power system stabilizer (PSS) in a multi machine power systems. The proposed adaptive method has an online controller, which the structure of is changed according to power system variations. This ability of adaptive controller leads to an adaptive performance proportionate with different loading conditions. In order to show effectiveness of the proposed method, it is compared with a conventional PSS tuned by using PSO (PSO-PSS). The simulation results show that the proposed method systematically deals with system uncertainties. The adaptive PSS can successfully damp out the oscillations, and shows a stronger performance than conventional PSS under different loading conditions.

Comparative seeker and bio-inspired fuzzy logic controllers for power system stabilizers

This paper compares the power system stabilizer based on sliding mode control with the fuzzy power system stabilizer for single machine infinite bus system (SMIB). Using the sliding mode control, a range is obtained for the changes in system parameters; and a stabilizer is designed to have a proper performance in this wide range. The purpose of designing the sliding mode stabilizer and fuzzy stabilizer is the increased stability and improving the dynamic response of the single machine system connected to the infinite bus in different working conditions. In this paper, simulation results are compared in case of conventional PSS, no PSS, PSS based on sliding mode control and PSS based fuzzy logic. The results of simulations performed on the model of nonlinear system shows good performance of sliding mode controller and the Fuzzy controller. SMIB system was selected because of its simple structure, which is very useful in understanding the effects and implications of the PSS.

In power system, the application of the power system stabiliser (PSS) has been proved to overcome the stability of power system. It is necessary to determine the appropriate PSS parameters. In this paper, a new cost function is presented for the tuning of PSS parameters. Optimisation of PSS parameters has been done by particle swarm optimisation algorithm. The power plant system that is simulated in this paper is one machine to infinite bus system. The responses of the PSS tuned with PSO and conventional power system stabiliser (CPSS) are compared with together.

In the past two decades, conventional power system stabilizer (PSS) is widely used to damp power systems oscillations. Nowadays, several approaches based on intelligent techniques have been applied to PSS design problem. This paper deals with optimal design of multimachine power system stabilizers to improve the dynamic stability of power system. The design problem is formulated as an optimization problem. Non-Dominated Sorting Genetic Algorithm (NSGA-II) is employed to search the optimal PSS parameters‥ Based on a three-machine nine-bus test system, nonlinear simulation results under disturbance, show the effectiveness of the proposed approach in power oscillation damping.