Adaptive Power System Stabilizer Research Articles

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.

Adaptive power system stabilizer with sliding mode for electric power systems

This work is focused on the design of a robust control for the excitation field voltage input to stabilize the rotor speed and angle in an electric power system with synchronous machine connected to an infinite bus. The complete 8th order plant model including the rotor and stator dynamics, is derived. Considering that the mechanical part model parameters are unknown, an observed-based adaptive control schemes is designed based on the plant complete model, Sliding Mode (SM) control and Adaptive Backstepping techniques. The effectiveness of the proposed adaptive control scheme is confirmed by simulation.

Explicit adaptive power system stabilizer design based an on-line identifier for single-machine infinite bus

This paper proposes an explicit adaptive controller to damp oscillations and to enhance the single machine infinite bus SMIB stability. Owing to the increasing requests for renewable energy and operating conditions, the identification for power systems has been increased recently. Changes in the power system parameters cause to use an explicit self-tuning control. The controller structure consists of combined on-line identifier and a feedback controller as PID and a radial basis function neural network (RBFNN) which acts as an adaptive power system stabilizer for SMIB. An adaptive linear neural network (ADALINE) depending on the input and output of open loop system is employed as on-line model identification to mimic on-line the SMIB output. The difference between SMIB and the identified model responses is used to adjust the ADALANN model weights on-line depending on a recursive least squares principle RLS and a recursive least square with adaptive directional forgetting RLSMadf. The particles swarm optimization (PSO) beside RLS and RLSMadf assess the weights of (RBFNN) and coefficients of PID controllers depending on the on-line ADALINE model weights. The proposed controller is validated with several operating conditions under various disturbances. The simulation results show the proposed controller whose parameters depend on on-line tuning techniques provides better performance than a conventional PID controller.

Adaptive Power System Stabilizer with Sliding Mode for Electric Power Systems

Adaptive Power System Stabilizer with Sliding Mode for Electric Power Systems

A model reference-based adaptive PSS4B stabilizer for the multi-machines power system

Two-inputs adaptive IEEE multi-bands power system stabilizer (PSS4B) was developed for oscillations damping control in power systems. Two supplementary loops based on model reference (MR) adaptive control were added to the typical PSS4B design. The MR has the same loops’ parameters of the typical PSS4B, and hence, avoiding a complex tuning process. The proposed PSS has a self-tuning gain reduction block to avoid any negative impact due to the high gains value during the disturbance time. The proposed PSS was applied on the four-machine benchmark power system. To evaluate the robustness of the proposed PSS, it was tested in comparison with the Delta W PSS, one-input multi-bands PSS4B (1iMB) and two-inputs multi-bands PSS4B (2iMB) stabilizers. The integration of the proposed PSS was demonstrating using different study cases. These cases consider the small-signal stability (SSS), large-signal stability (LSS) and the coordination test for the local and inter-area excited power modes. The proposed PSS demonstrated robust and superior responses in all cases.

Adaptive Fuzzy Type-2 Synergetic Control Based on Bat Optimization for Multi-Machine Power System Stabilizers

A new, adaptive, fuzzy type-2 fast terminal, synergetic multi-machine power system stabilizer is proposed in this study, based on the Bat algorithm. The time spent to reach the equilibrium point, from any initial state, is guaranteed to be finite. The adaptive fuzzy type-2 design is applied to estimate the unknown functions of a multi-machine power system. The parameters of the fast terminal synergetic control are optimized, using bat metaheuristic method. In order to test the robustness of the proposed stabilizer, three load conditions, of the multi-machine power system are studied. A comparison of the proposed adaptive fuzzy type-2 synergetic power system stabilizer with bat conventional approach is presented, indicating improved performance. The control system stability is assessed by the second theorem of Lyapunov and is proven to be asymptotically stable.

Influence of Adaptive Power System Stabilizer on the Transient and Dynamic Performance of a Multimachine System

This paper presents a power system stabilizer (PSS) for improving the performance of a multimachine system when the system is subjected to different types of disturbances. An adaptive proportional-plus-derivative-plus-integral (PID) PSS is proposed in this paper. In this technique, the controller parameters (proportional, integral, and derivative gains) are not fixed but they are varying according to the system operating conditions. The derivative of power angle, error in output power, terminal voltage, and error in power angle are selected to be the input signals to the proposed stabilizer. A weighting factors are assigned to these signals to obtain the best performance characteristics of each machine. The obtained computer results from simulation study are compared with those of a conventional lead-lag stabilizer.

Application of affine NARMA model to design of adaptive power system stabilizer

Application of affine NARMA model to design of adaptive power system stabilizer

Transient and Dynamic Stability Improvement of a Single Machine Infinite Bus Power System using Adaptive Fractional Order Proportional Integral Derivative Power System Stabilizer

Abstract: This paper presents a study of the transient and dynamic stability enhancement and control of a synchronous generator connected to an infinite bus (single machine infinite bus system) via two parallel transmission lines when the power system working under different operating conditions and subjected to different disturbances. An effective mean of damping the oscillations resulting from these disturbances is to provide the synchronous generator with power system stabilizer. An adaptive fractional order proportional integral derivative controller is suggested to play the role of power system stabilizer in this paper. The results obtained from simulation study are presented and discussed.

Transient and Dynamic Stability Improvement of a Single Machine Infinite Bus Power System using Adaptive Fractional Order Proportional Integral Derivative Power System Stabilizer

Transient and Dynamic Stability Improvement of a Single Machine Infinite Bus Power System using Adaptive Fractional Order Proportional Integral Derivative Power System Stabilizer

Adaptive Fuzzy Gain of Power System Stabilizer to Improve the Global Stability

The lead-lag power system stabilizer has several parameters to be optimized.In fact, the number of these latter increases with the number of generators constituting the multi-machine system.In this work, we propose anew approach of an adaptive and robust PSS; it achieves encouraging results by adjusting the gain using fuzzy logic and in the same time we use the same PSSs for each machine. In the first place, we could check that the gain is among the most critical parameters of the lead lag PSS. The parameters are globally optimized by the genetic algorithm, after that an expertise on the speed and the gain variations allow the value prediction according to the velocity deviation. To validate our results, a robustness test was made on a multimachine system IEEE (3 machines 9 bus), for different loads and the results showed good performance and robustness of the presented PSS.

Interarea Power System Oscillations Damping via AI-based Referential Integrity Variable-Structure Control

Abstract The design of power system stabilizer (PSS) is load-dependent and needs continuous adjustment at each operating condition. This paper aims at introducing a robust non-fragile PSS for interconnected power systems. The proposed controller has the capability of adaptively tuning online its rule-base through a variable-structure direct adaptive control algorithm in order to rigorously attain the desired objectives. The PSS controller acts on damping the electromechanical modes of oscillations not only through a wide range of operating conditions but also in presence of different disturbances. Using MATLABTM-Simulink, simulation results significantly verify that the proposed controller provides favorable performance and efficiently contributes towards enhancing the system dynamic behavior when applied to the four machines two-area power system that mimics the typical system behavior in actual operation. The interaction between the variable-structure adaptive fuzzy-based power system stabilizer (VS-AFPSS) and the existed typical ones inside the interconnected power systems has been explicitly discussed. Compared to other conventional controllers, VS-AFPSS enables better damping characteristics to both local and inter-area oscillation modes considering different operating conditions and sever disturbances.

Predictive optimized adaptive PSS in a single machine infinite bus

Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison.

Reaching phase free adaptive fuzzy synergetic power system stabilizer

Abstract In this paper, an adaptive fuzzy power system stabilizer is developed based on robust synergetic control theory and terminal attractor techniques. The main contribution consists in making the dynamic system insensitive to parameters variation. This aim is achieved using a new synergetic controller design such that power system states start, evolve and remain on a designer chosen attractor toward the equilibrium point therefore avoiding transient mode. Rendering the design more robust, fuzzy logic systems are used to approximate the unknown power system dynamic functions without calling upon usual model linearization and simplifications. Based on an indirect adaptive scheme and Lyapunov theory, adaptation laws are developed to make the controller handle parameters variations due to the different operating conditions occurring on the power system and to guarantee stability. 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 show the effectiveness and robustness of the proposed stabilizer in damping power system oscillations under various disturbances and better overall performance than classical PSS and some other types of power stabilizers.

A Novel Adaptive Wide Area PSS Based on Output-Only Modal Analysis

Usage of wide area PSSs (WAPSS) in actual power systems is limited because of their restricted adaptability to different operating conditions. Numerous adaptive control methods have been proposed to solve this problem, but they are limited due to strict prerequisites, such as the necessity of consistent excitations or large disturbances. This paper, therefore, presents a novel adaptive wide area PSS (AWAPSS), which has the ability of tracking system operating condition without the need for meeting the above prerequisites. The inherent dead-band structure of a WAPSS enables a steady system to perform like in an open loop, thus allowing the parameters of a WAPSS to be tuned adaptively through output-only modal analysis. The effectiveness of the novel AWAPSS has been validated in a two-area four-machine system as well as in a large complex system, China Southern Grid.

Design and Experimental Tests of an LPV Power System Stabilizer on a 10kVA Small-scale Generating Unit

In this paper, the application of linear parameter-varying (LPV) identification and control methods for designing and performance evaluation of an adaptive power system stabilizer (PSS) is presented. The target control objective is to improve the damping of the dominant electromechanical oscillating mode in the power system. The performance of the LPV PSS controller has been assessed by means of experimental tests carried out on 10 kVA small-scale power system. For design purposes, an LPV ARX model was estimated from experimental tests, for a wide range of operating conditions. The LPV controller was tuned via an optimization problem, in the form of a Parameterized Linear Matrix Inequality (PLMI). The solution was obtained through a sum-of-squares relaxation. Both the LPV model and the LPV-PSS have an explicit dependency on system scheduling variables, namely the active and reactive powers measurements. Therefore, the LPV-PSS was designed to ensure stability and performance for a wide range of operating conditions, an objective usually difficult to obtain by using fixed parameter controllers.

Direct adaptive power system stabilizer design using fuzzy wavelet neural network with self-recurrent consequent part

This paper aims to propose a stable fuzzy wavelet neural-based adaptive power system stabilizer (SFWNAPSS) for stabilizing the inter-area oscillations in multi-machine power systems. In the proposed approach, a self-recurrent Wavelet Neural Network (SRWNN) is applied with the aim of constructing a self-recurrent consequent part for each fuzzy rule of a Takagi-Sugeno-Kang (TSK) fuzzy model. All parameters of the consequent parts are updated online based on Direct Adaptive Control Theory (DACT) and employing a back-propagation-based approach. The stabilizer initialization is performed using an approach based on genetic algorithm (GA). A Lyapunov-based adaptive learning rates (LALRs) algorithm is also proposed in order to speed up the stabilization rate, as well as to guarantee the convergence of the proposed stabilizer. Therefore, due to having a stable powerful adaptation law, there is no requirement to use any identification process. Kundur's four-machine two-area benchmark power system and six-machine three-area power system are used with the aim of assessing the effectiveness of the proposed stabilizer. The results are promising and show that the inter-area oscillations are successfully damped by the SFWNAPSS. Furthermore, the superiority of the proposed stabilizer is demonstrated over the IEEE standard multi-band power system stabilizer (MB-PSS), and the conventional PSS.

An Add-On Self-Tuning Control System for a UPFC Application

This paper presents an add-on self-tuning (ST) control scheme for a Unified Power Flow Controller (UPFC) to assist its conventional PI control system in damping power oscillations. The ST control algorithm is based on a Pole Shift (PS) technique that has previously been successfully applied in Adaptive Power System Stabilizers (APSSs). For a wide range of operating conditions, the conventional PI-UPFC unless returned suffers from insufficient/nonoptimal damping performance. To overcome this problem, the authors propose supplementing the PI controllers with an ST feedback loop comprised of an identifier and a PS control algorithm. With a CRLS identifier tracking the system conditions online, this scheme eliminates the need for PI parameter retuning. Further, to correctly identify system parameters during large disturbances, a constrained recursive least squares (CRLS) identification procedure is adopted here. An improved damping performance with the proposed add-on scheme assisting the nonoptimal PI-UPFC is demonstrated for a two-area power system.

Adaptive Power System Stabilizer Design Using Optimal Support Vector Machines Based on Harmony Search Algorithm

—This article presents the application of support vector machines to adaptive power system stabilizer design in a multi-machine power system based on the harmony search algorithm. Data from a multi-machine power system are the input features of the support vector machines. Support vector machine parameters and power system features are simultaneously optimized by harmony search based on the k-fold cross-validation technique. The proposed algorithm is trained by the optimal support vector machine parameters and optimal power system features. Power system stabilizer parameters produced by the proposed algorithm can be adapted by various operating conditions when the power system operates either inside or outside the training ranges. Simulation studies in the IEEJ Western Japan ten-machine power system demonstrate that the proposed algorithm is far superior to conventional power system stabilizers with fixed parameters and those designed by a robust coupled vibration model under various operating conditions and severe disturbances.

Adaptive robust PSS to enhance stabilization of interconnected power systems with high renewable energy penetration

Today, the penetration of renewable energies in power system significantly increases. However, the intermittent power of renewable energies may cause severe problems of low frequency oscillations in interconnected power systems due to insufficient system damping. Moreover, the operating condition of power system may change any time. This paper proposes a design of adaptive robust power system stabilizer (PSS) to damp low frequency oscillations in an interconnected power system with high renewable energy (RE) penetration. System identification is used to construct an estimated model, and the estimated model will be updated whenever the estimated mismatch exceeds predetermined bound. Based on the estimated model, the PSS controller of each generator will be re-tuned using a genetic algorithm. The optimization problem is formulated to guarantee the robustness of PSS and to increase the damping ratio of the dominant mode. In this work, we also install a memory so that several models and corresponding PSS parameter sets can be stored in the memory and re-used in the similar situations. Moreover, the PSSs on generators are able to control without communications among them; it will reduce investment cost significantly. The performance, effectiveness and robustness of the proposed method have been investigated in an interconnected power system in comparison with a conventional PSS (CPSS). Simulation results confirm that the damping effects of the proposed PSS are much better than that of the CPSS against various operating conditions and system uncertainties.