Power System Stabilizer Design Research Articles

Coordination of Controllers to Development of Wide-Area Control System for Damping Low-Frequency Oscillations Incorporating Large Renewable and Communication Delay

AbstractThe modern power systems incorporate high penetration of renewable is a large, composite, interconnected network with dynamic behavior. The small disturbances occurring in the system may induce low-frequency oscillations (LFOs) in the system. If the (LFOs) are not suppressed within a stipulated time, it may cause system islanding or even blackouts. Hence, it is essential to investigate the behavior of the system under various levels of disturbances and control action must be taken to damp these oscillations. The established approach to damping the LFOs is by installing power system stabilizers (PSS). PSS uses the local signals from generators to control the oscillations. The dominant source of inter-area oscillations in power systems is due to overloaded weak interconnected lines, converter-interfaced generation, and the action of the high gain exciter present in the system. Consequently, wide area control is needed to control the inter-area oscillations existent in the system. This paper developed a coordinated design of conventional PSS, static compensator, renewable converters, and wide area controller for damping the local and inter-area oscillations in renewable incorporated power systems. The performance of the developed controller is evaluated through the time domain analysis and eigenvalue analysis. A comparison of the introduced controller has been done with other standard conventional methods. The choice of input signals for the wide area controller from the wide-area measurement system is done based on the controllability index. Additionally, the location of the controller must be identified to dampen the inter-area oscillations in the system. In this paper, the controllability index is calculated to find out the highly affected wide area signals for considering it as the feedback signal to a developed controller. The location of the controller is recognized by computing the participation factor. The developed controller has experimented on renewable incorporated large study power systems when time delay and noise are present in wide area signals.

STABILISATEUR DE SYSTÈME D'ALIMENTATION ROBUSTE BASÉ SUR UN CONTRÔLE H∞ STRUCTURÉ POUR LA STABILITÉ D'UN SYSTÈME MULTI-MACHINE

A robust design of power system stabilizers (PSSs) using H∞ output feedback control has been introduced in this work. To facilitate the implementation of the designed PSSs, the proposed technique employs the H∞ to tune the fixed-structure conventional lead-lag PSS parameters of the multi-machine system. These PSSs are used to improve the damping of the local and inter-area low-frequency oscillations in power systems under different operating conditions. The proposed control is tested on a multi-machine system, which is a three-machine nine-bus system. A comparative simulation study shows a significant enhancement and good performance of the proposed design compared to an IEEE conventional power system stabilizer.

Design of Power System Stabilizer for DFIG-based Wind Energy Integrated Power Systems Under Combined Influence of PLL and Virtual Inertia Controller

Design of Power System Stabilizer for DFIG-based Wind Energy Integrated Power Systems Under Combined Influence of PLL and Virtual Inertia Controller

A convolutional neural network framework to design power system stabilizer for damping oscillations in multi-machine power system

A convolutional neural network framework to design power system stabilizer for damping oscillations in multi-machine power system

Robust multi-machine power system stabilizer design using bio-inspired optimization techniques and their comparison

This paper reports a comparative study among four bio-inspired meta-heuristic techniques i.e. Sooty-Tern Optimization (STO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to tune the robust Power System Stabilizer (PSS) parameters of the multi-machine power system. These approaches are successfully tested on two bench-mark systems: sixteen-machine, sixty-eight-bus New England Extended Power Grid (NEEPG) and three-machine, nine-bus Western System Coordinating Council (WSCC). The efficacy of planned PSS via STO and GWO is validated by extensive non-linear simulations, eigenvalue analysis, and performance indices for numerous operating conditions under decisive perturbations, and outcomes are matched with those of GA and PSO techniques. In addition, the robustness is also tested for these algorithms. The results indicate that the PSS design using STO and GWO improves the small-signal stability and damping performance for mitigating inter-area and local area modes of low-frequency oscillations compared to GA and PSO.

“Enhancing power system stability: an innovative approach using coordination of FOPID controller for PSS and SVC FACTS device with MFO algorithm”

This paper investigates an optimal methodology for mitigating low-frequency oscillation concerns in power systems. The study explores the synergistic integration of a power system stabilizer (PSS) and a flexible alternating current transmission system (FACTS) to formulate an intelligent controller. A comprehensive analysis encompasses various PSS design strategies, including lead-lag (LL), proportional-derivative-integral (PID), and fractional-order proportional-integral-derivative (FOPID) controllers. The FACTS device selected for this investigation is a static VAR compensator (SVC), highlighting the exceptional efficacy of FOPID-based PSS over alternative strategies with a power oscillation damper. The study extends its scope to encompass a comparative assessment of two distinct optimization algorithms: the moth flame optimization (MFO) and the antlion optimization (ALO). The research is conducted using a single-machine infinite bus power system (SMIB) as the case study platform. A total of four diverse test scenarios are executed under varying operating conditions. The evaluation of the developed method employs six distinct performance indices to investigate the developed controller thoroughly. The outcomes reveal that the MFO-optimized FOPID-PSS and SVC controller outperforms other control schemes. This optimized configuration demonstrates substantial improvements across all performance indices. These findings underscore the superior capabilities of the proposed approach in enhancing power system stability and performance.

Power System Stability Enhancement Using Grasshopper Optimization Approach and PSSs

A new meta-heuristic algorithm namely Grasshopper Optimization Approach (GOA) for Power System Stabilizer (PSS) design problem is investigated in this paper. The parameters of PSSs are optimized by GOA to minimize the time domain objective function. The performance of the designed GOA based PSSs (GOAPSS) has been has been compared with Differential Evolution (DE) based PSSs (DEPSS) and the Particle Swarm Optimization (PSO) based PSSs (PSOPSS) under various loading events. The results of the proposed GOAPSS are confirmed via eigenvalues, damping ratio, time domain analysis, and performance indices. Moreover, the robustness of the GOA in getting good damping characteristics is verified.

Recurrent neural network based design of fractional order power system stabilizer for effective damping of power oscillations in multimachine system

The complexity of modern power systems has risen due to the growing demand for electricity. To mitigate this problem, the role of the electric utility in supplying safe and reliable electricity has become increasingly crucial. Low-frequency oscillations (LFOs) in a power system are an inevitable aspect. Therefore, the reliability of the system requires appropriate damping to overcome these LFOs. This paper proposes a novel design methodology for a fractional-order power system stabilizer (FO-PSS) to enhance the stability of the power system network. FO-PSS is designed to effectively dampen LFOs in both single-machine infinite bus systems (SMIB) and multi-machine power systems (MMPS). Recurrent neural network (RNN) is used to predict the parameters of proposed PSSs. To evaluate the efficacy of the proposed PSS, various test cases are considered. The results are compared to those obtained from traditional PSSs and optimization based PSSs. The effectiveness of the proposed RNN-based FO-PSS is demonstrated under diverse loading conditions.

Artificial Eco-System-Based Optimization Algorithm for Optimal Design of Single-Machine Infinite Bus and Multi-Machine Power System Stabilizers

Artificial Eco-System-Based Optimization Algorithm for Optimal Design of Single-Machine Infinite Bus and Multi-Machine Power System Stabilizers

LSTM based deep neural network model of power system stabilizer for power oscillation damping in multimachine system

AbstractPower system oscillation is an unavoidable threat to the stability of an interconnected modern power system. The reliable operation of a modern power system is widely related to the dampening of electromechanical low‐frequency oscillations (ELFOs). These ELFOs must be dampened appropriately to maintain the stability and reliability of the system. However, it is relatively difficult to resolve the problem of ELFOs completely with traditional power system stabilizers (PSSs). Consequently, research should be directed towards the development of efficient damping controllers, or PSSs, for power oscillation damping. Motivated from the aforementioned fact, this article presents the design of a proportional integral derivative power system stabilizer (PID‐PSS) via a long short‐term memory neural network (LSTM) based deep neural approach for damping power system oscillations in interconnected power systems. LSTM is used to train the parameters of PID‐PSS. To evaluate the performance of the proposed LSTM based PID‐PSS, diverse test cases under different operating conditions are examined. Further, the performance of the proposed LSTM based PID‐PSS is compared with traditional PSSs through time‐domain simulations. The test cases reveal the desired efficiency achieved by the proposed LSTM based PID‐PSS under diverse loading conditions.

Power System Stabilizer Design using Genetic Algorithms and Particle Swarm Optimization

in this paper, Meta-heuristic techniques using genetic algorithms GA and particle swarm optimization PSO to tuning optimal design of power system stabilizer PSS proposed. This latter have been used for many years to add damping to electromechanical oscillations of power system, Based on this idea we have proposed multiobjective function composed with tow function, first maximize stability margin by increasing the damping factors while minimizing the real parts of the eigenvalues. Simulation results to comparative study between genetic algorithms and particle swarm optimization obtained by our realized graphical user interface (GUI) proved the efficiency of PSS optimized by genetic algorithms in comparison with Particle Swarm Optimization, showing stable system responses almost insensitive to large parameter variations and under different operating regime (under-excited, nominal and over excited regime).

Power system stabilizer design for ideal AVR using local measurements

In this work, the application of an Ideal automatic voltage regulator is presented for an interconnected power system. The Ideal AVR is designed using the feedback linearization technique and it is shown that the voltage regulation response with the Ideal AVR is superior to conventional linear AVR. Subsequently, a power system stabilizer is added to improve the small signal stability. The proposed control scheme is demonstrated to provide vastly superior voltage regulation and damping of the rotor mode compared to conventional control. Simulation results are presented using a sub-transient (6th order) model of the IEEE 14 generator 59 bus system.

Implementing Optimization Techniques in PSS Design for Multi-Machine Smart Power Systems: A Comparative Study

This study performed a comparative analysis of five new meta-heuristic algorithms specifically adopted based on two general classifications; namely, nature-inspired, which includes artificial eco-system optimization (AEO), African vulture optimization algorithm (AVOA), gorilla troop optimization (GTO), and non-nature-inspired or based on mathematical and physics concepts, which includes gradient-based optimization (GBO) and Runge Kutta optimization (RUN) for optimal tuning of multi-machine power system stabilizers (PSSs). To achieve this aim, the algorithms were applied in the PSS design for a multi-machine smart power system. The PSS design was formulated as an optimization problem, and the eigenvalue-based objective function was adopted to improve the damping of electromechanical modes. The expressed objective function helped to determine the stabilizer parameters and enhanced the dynamic performance of the multi-machine power system. The performance of the algorithms in the PSS’s design was evaluated using the Western System Coordinating Council (WSCC) multi-machine power test system. The results obtained were compared with each other. When compared to nature-inspired algorithms (AEO, AVOA, and GTO), non-nature-inspired algorithms (GBO and RUN) reduced low-frequency oscillations faster by improving the damping of electromechanical modes and providing a better convergence ratio and statistical performance.

Design and Optimal Location of Power System Stabilizer in the Multi-Machine Power Network

This paper proposes a damping torque index (DTI) to determine the optimal installation location of the power system stabilizer (PSS) in the multi-machine power network. The proposed index is based on the classical damping torque analysis (CDTA) method for power system low-frequency electro-mechanical (LFEO) analysis. The selection criteria of the PSS location is the maximum magnitude of DTI under normal operating conditions. The CDTA method is used to design PSS, and the phase compensation technique subsequently adjusts the associated parameters. Furthermore, to analyze the power system’s critical oscillation mode, a wide-area damping controller (WADC) is design for the synchronous generator where optimal location of PSS is install. The reduced-order model-based WADC includes time-varying delay in the wide-area signal. The WADC’s input signals from the phasor measurement unit (PMU) and the location of the PMU are selected using geometric measures of observability and WADC parameters design based on the residue approach. The proposed approach is validated in two separate test systems, and modal analysis is carried out on MATLAB software. The simulated results have been validated on the real-time digital simulator (RTDS) RSCAD 5.012. Results obtained on RTDS show that the proposed approach efficiently damps low-frequency electro-mechanical oscillations.

Indirect adaptive fuzzy finite time synergetic control for power systems

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults. Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems. Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Low frequency oscillations damping by design of power system stabilizer using intelligent controllers

The intention and justification of a Fuzzy and PID Controller based PSS for a multi area classification is to examine its analysis to dank out the squat frequency oscillation. The design employs a conservative input pairs like speed deviation (Δω) and rotor angle deviation (Δδ) to the Fuzzy PSS and speed deviation (Δω) for Integer Order PID (IOPID) controller. The advantage of this Fuzzy based PSS is that, it can be fed to each of machines in the each areas of the Power System which eases cost, scanning time and thus shortens the arrangement. It is observed that Fuzzy based PSS yields a more satisfactory role in damping low frequency oscillations and to increase stability rather than conventional and IOPID PSS. The analysis of the system is done using MATLAB 2014b.

A Recent Review on Approaches to Design Power System Stabilizers: Status, Challenges and Future Scope

Modern power system networks are complex and subjected to several uncertainties. Due to the complexity and uncertainties involved in power system operation, the networks are prone to instabilities. Rotor-angle instability is one such issue that, if not addressed properly, may lead to system collapse. A power system stabilizer (PSS) is primarily a power oscillation damping (POD) controller used to dampen power oscillations, thereby improving rotor angle stability. The proper design of PSSs is a challenging task and is essential for the secure and reliable operation of power systems. In the past, many power system instability events occurred, resulting in cascading failures and even blackouts. In the literature, several methods are proposed for the efficient design of PSSs or POD controllers. In this contribution, a recent review on the design of PSS is presented, along with challenges and the future scope of research in this field. On the basis of this review, it can be concluded that there is ample scope for designing PSS in a more efficient and robust manner, considering several uncertainties that may occur during the operation of modern power systems.

Optimal Design of Damping Control of Oscillations in Power System Using Power System Stabilizers with Novel Improved BBO Algorithm

Studies on power system stability are necessary for power network development & operation. Due to the great dimensionality and complexity of contemporary power systems, its significance has increased. The stability of an interconnected power system is seriously threatened by power system oscillation. Numerous strategies based on contemporary control theory, intelligent control, and optimization methods have been applied to the Power system stabilizers (PSSs) design problem recently. Each categorization contains a number of design techniques that increase the PSS's effectiveness and sturdiness in damping off low frequency vibrations. This work presents a new Modified and Improved Biogeography-Based Optimization (MIBBO) method to increase the optimization effectiveness of the usual Biogeography-Based Optimization (BBO) technique applied for the optimization of the parameters of the PSSs & Proportional Integral Derivative (PID) controller under the non-linear loading (NLL) conditions. The performance parameters which are obtained by the MIBBO based controller are compared with the results of normal BBO Method, Particle Swarm Optimization method (PSO) and Adaptation Law (AL) method. To justify the success and correctness of the proposed control approach, Matlab simulation results-based study of all the above-mentioned techniques is made and reported.

Power System Stabilizers Design Using BAT Algorithm

A new metaheuristic method, the BAT algorithm based on the echolocation behaviour of bats is proposed in this paper for optimal design of Power System Stabilizers (PSSs) in a multimachine environment. The PSSs parameter tuning problem is converted to an optimization problem which is solved by the BAT search Algorithm. An eigenvalues based objective function involving the damping factor, and the damping ratio of the lightly damped electromechanical modes is considered for the PSSs design problem. The performance of the proposed BAT based PSSs (BATPSS) has been compared with Genetic Algorithm (GA) based PSSs (GAPSS) and the Conventional PSSs (CPSS) under various operating conditions and disturbances. The results of the proposed BATPSS are demonstrated through time domain analysis, eigenvalues and performance indices. Moreover, the results are presented to demonstrate the robustness of the proposed algorithm over the GA and conventional one.

Power System Stability Improvement of FACTS Controller and PSS Design: A Time-Delay Approach

The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control to augment with an automatic voltage regulator (AVR) supplemental feedback stabilizing signal. This paper proposes a new strategy for simultaneously tuning the power system stabilizer (PSS) and FACTS controller, considering time delays. The design of the proposed controller is modeled as an optimization problem, and the parameters of the controller are optimized through the grasshopper optimization algorithm (GOA). The suggested controller’s efficacy is evaluated for both single-machine infinite bus systems and multi-machine power systems under various disturbances. It also investigated the performance of the proposed controller with variations in signal transmission delays. The results obtained from GOA optimized proposed controller are compared with those obtained from the differential evolution algorithm, genetic algorithm, and whale optimization algorithm. In this context, the proposed GOA optimized controller reduced the objective function value by 16.32%, 14.56%, and 13.72%, respectively, in the SMIB system and 1.41%, 9.98%, and 13.31%, respectively, for the multi-machine system compared with the recently published WOA, and the well-established GA and DE. Further, the proposed controller is found to be stable and effectively increases stability even under small disturbances.