Conventional Power System Stabilizer Research Articles

Adaptive self-tuning PID fuzzy sliding mode control for mitigating power system oscillations

In this paper, an adaptive self-tuning PID fuzzy sliding mode controller (ASPFSM) with a PID switching surface is proposed to damp power system oscillations. To overcome the problems in the design of a sliding-mode controller, which are the supposition of known uncertainty bounds and the chattering phenomenon in the control effort, an adaptive self-tuning PID based Lyapunov theory is studied. An adaption law is obtained from the Lyapunov stability theory, so the stability of the closed-loop system can be guaranteed. Then, the effectiveness of the ASPFSM is studied under different situations of a two-area four-machine power system. The simulation results confirm that performance of ASPFSM is much better than conventional power system stabilizer (CPSS).

Simulation of novel hybrid method to improve dynamic responses with PSS and UPFC by fuzzy logic controller

In this paper, a hybrid method is proposed to damp frequency and power oscillations in the power system equipped with unified power flow controller (UPFC) and power system stabilizer (PSS) controllers. The method is robust with respect to operating point’s changes. This hybrid method consists of two stages: offline and online. In the offline stage, the coefficients of PSS and UPFC controllers for different operating points have been found by PSO algorithm; then in the second stage, online new fuzzy controller is proposed to select the best PSS and UPFC coefficients according to operating point. The proposed method is simulated for single machine infinite bus system-associated PSS and UPFC for three different operating points in MATLAB software, and results of proposed method simulation are investigated and compared with conventional PSS (CPSS) + UPFC, CPSS controllers. Simulation results show that the proposed method has a better performance.

Switching power system stabilizer and its coordination for enhancement of multi-machine power system stability

This paper proposes a coordinated switching power system stabilizer (SPSS) to enhance the stability of multimachine power systems. The SPSS switches between a bang-bang power system stabilizer (BPSS) and a conventional power system stabilizer (CPSS) based on a state-dependent switching strategy. The BPSS is designed as a bang-bang constant funnel controller (BCFC). It is able to provide fast damping of rotor speed oscillations in a bang-bang manner. The closed-loop stability of the power system controlled by the SPSSs and the CPSSs is analyzed. To verify the control performance of the SPSS, simulation studies are carried out in a 4-generator 11-bus power system and the IEEE 16-generator 68-bus power system. The damping ability of the SPSS is evaluated in aspects of small-signal oscillation damping and transient stability enhancement, respectively. Meanwhile, the coordination between different SPSSs and the coordination between the SPSS and the CPSS are investigated therein.

Power System Stabilizer Design Based on a Particle Swarm Optimization Multiobjective Function Implemented Under Graphical Interface

Power system stability considered a necessary condition for normal functioning of an electrical network. The role of regulation and control systems is to ensure that stability by determining the essential elements that influence it. This paper proposes a Particle Swarm Optimization (PSO) based multiobjective function to tuning optimal parameters of Power System Stabilizer (PSS); this later is used as auxiliary to generator excitation system in order to damp electro mechanicals oscillations of the rotor and consequently improve Power system stability. The computer simulation results obtained by developed graphical user interface (GUI) have proved the efficiency of PSS optimized by a Particle Swarm Optimization, in comparison with a conventional PSS, showing stable system responses almost insensitive to large parameter variations.Our present study was performed using a GUI realized under MATLAB in our work.

Power System Stabilizer Design Based a PSO Multiobjective Function Implemented Under Graphical Interface

Power system stability considered a necessary condition for normal functioning of an electrical network. The role of regulation and control systems is to ensure that stability by determining the essential elements that influence it. This paper proposes a Particle Swarm Optimization (PSO) based multiobjective function to tuning optimal parameters of Power System Stabilizer (PSS); this later is used as auxiliary to generator excitation system in order to damp electro mechanicals oscillations of the rotor and consequently improve Power system stability. The computer simulation results obtained by developed graphical user interface (GUI) have proved the efficiency of PSS optimized by a Particle Swarm Optimization, in comparison with a conventional PSS, showing stable system responses almost insensitive to large parameter variations.Our present study was performed using a GUI realized under MATLAB in our work.

Power system stabilizer design based on optimal model reference adaptive system

Abstract This paper addresses an optimal model reference adaptive system (MRAS) to design power system stabilizer (PSS) in multi-machine electric power systems. Weighting factors of the proposed MRAS are adjusted by particle swarm optimization (PSO) as well as its input signal is limited by a normalization technique to assure network stability. The proposed modified-optimal MRAS-PSS is evaluated against conventional PSS to demonstrate its advantages. In order to investigate the performance of the proposed MRAS-PSS under parametric uncertainties, three operating conditions are defined and simulated. Several nonlinear and time-domain simulations are carried out to validate the viability and effectiveness of the proposed MRAS-PSS under network uncertainties.

An Efficient Enhancement of Rotor Angle Stability using a Hybrid BBO-DE Approach

Power System Stabilizers (PSS) are mainly used as add-on controllers to damp out the low frequency oscillations in the power system stability operation. The tuning of Conventional Power System Stabilizer (CPSS) parameters for a system should be robust such that overall system stability phenomena can be improved. In the recent decades, various population based heuristic algorithms are available to sort out the stability problem in the electric Power System (PS). In this paper presents a new heuristic optimization algorithm named as hybrid Biogeography Based Optimization adapted Differential Evolution (BBO-DE) algorithm for finding the optimal CPSS parameters for Single Machine Infinite Bus (SMIB) and multi-machine system under various operating conditions. The location of the PSS has been carried by participation factor and optimal design of PSS parameters have been obtained by its eigen value approach. Simulations are carried out for the SMIB and three machine nine bus systems. The proposed hybrid BBO-DE technique is robust and highly efficient as compared with its related heuristic algorithms such as Biogeography Based Optimization involved Power System Stabilizer (BBOPSS) and Differential Evolution based Power System Stabilizer (DEPSS). From the simulation results the proposed method enhances the dynamic stability of the system remarkably, especially when the system operating condition changes.

An interval type-2 fuzzy logic PSS with the optimal H∞ tracking control for multi-machine power system

In this paper, the interval type-2 fuzzy logic controller IT2FLC as a power system stabiliser PSS combined with the optimal H∞ tracking control is proposed in this study. The multi-machine power system is considered for evaluation and implementation of the robust proposed controllers. The type-2 fuzzy logic based on interval value sets is capable for modelling the uncertainty and imprecision and to overcome the drawbacks of the conventional PSS. The input signals to the IT2FLC are considered as speed deviation and acceleration. The optimal H&infin tracking control guarantees the convergence of the errors to the neighbourhood of zero. The objective of the proposed method is to enhance the stability and the dynamic response of the multi-machine power system in different operating conditions. The performance with IT2FL-PSS and H∞ is compared to the performance of the power system with IT1FL-PSS and H∞ and with conventional PSS. In order to test the effectiveness of the proposed method, the simulation results show the damping of the oscillations of the angle and angular speed with reduced overshoots and quick settling time.

An interval type-2 fuzzy logic PSS with the optimal H∞ tracking control for multi-machine power system

In this paper, the interval type-2 fuzzy logic controller (IT2FLC) as a power system stabiliser (PSS) combined with the optimal H∞ tracking control is proposed in this study. The multi-machine power system is considered for evaluation and implementation of the robust proposed controllers. The type-2 fuzzy logic based on interval value sets is capable for modelling the uncertainty and imprecision and to overcome the drawbacks of the conventional PSS. The input signals to the IT2FLC are considered as speed deviation and acceleration. The optimal H&infin tracking control guarantees the convergence of the errors to the neighbourhood of zero. The objective of the proposed method is to enhance the stability and the dynamic response of the multi-machine power system in different operating conditions. The performance with (IT2FL-PSS and H∞) is compared to the performance of the power system with (IT1FL-PSS and H∞) and with conventional PSS. In order to test the effectiveness of the proposed method, the simulation results show the damping of the oscillations of the angle and angular speed with reduced overshoots and quick settling time.

BBO algorithm-based tuning of PID controller for speed control of synchronous machine

A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1–2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.

A multiobjective tuning approach of power system stabilizers using particle swarm optimization

This work presents an optimal tuning approach of power system stabilizers (PSSs) using multiobjective particle swarm optimization. Two types of PSSs are investigated, the conventional speed-based PSS type and a dual-input PSS type that uses the accelerating power as an additional input. The tuning problem of these PSSs is formulated as a minimization problem of a vector objective function characterizing the damping and the transient performance of the closed-loop system. A 3-machine 9-bus power system example is considered, and the speed-constraine multiobjective particle swarm optimization algorithm is used to solve the optimization problem. The results show that trade-offs exist between the 2 objective functions of the problem, and that the best trade-off is obtained with the dual-input PSS. The performance of the resulting PSSs is illustrated through numerical simulations considering different scenarios.

Small Signal Stability Analysis of DFIG Fed Wind Power System Using a Robust Fuzzy Logic Controller

This paper focuses on the small signal stability analysis of Doubly-Fed Induction Generator (DFIG) fed wind power system under three modes of operation. The system stability is affected by the influence of electromechanical oscillations, which can be damped using Power System Stabilizer (PSS). A detailed modeling of DFIG fed wind system including controller has been carried out. The damping controller is designed using fuzzy logic to damp the oscillatory modes for stability. The robust performance of the system with controllers has been evaluated using eigen value analysis and time domain simulations under various disturbances and wind speeds. The effectiveness of the proposed fuzzy based PSS is compared with the performance of conventional PSS implemented in the wind system.

A novel chaotic teaching–learning-based optimization algorithm for multi-machine power system stabilizers design problem

This paper proposes an efficient optimization algorithm named chaotic teaching–learning algorithm (CTLA), to solve multimachine power system stabilizers design problem. The original teaching learning algorithm as competitive to other optimization algorithms, used two phases to proceed to the global optimal solution: ‘teacher phase’ and ‘learner phase’. However, during the second phase an adequate interaction between the teacher and the learners in entire search space are not guaranteed and the algorithm may be trapped in local optima. Thus, in the proposed CTLA a new phase named “chaotic phase” is added in order to overcome this drawback. The performance of the CTLA is investigated by using a set of benchmark functions. To demonstrate the effectiveness of the proposed algorithm in power systems, the conventional lead-lag power system stabilizers (PSSs) are tuned for: three machines nine bus system (WSCC) and the ten machine thirty-nine bus New England power systems. The performance of the proposed CTLA-based PSS (CTLAPSSs) under different loading conditions and disturbances is investigated through eigen-value analysis, non-linear time domain-simulations and some performance indices.

Coordinated design of power system stabilizers and TCSC employing improved harmony search algorithm

Power System Stabilizers (PSS) are generally employed to damp electromechanical oscillations by providing auxiliary stabilizing signals to the excitation system of the generators. But it has been found that these Conventional PSS (CPSS) do not provide sufficient damping for inter-area oscillations in multi-machine power systems. Thyristor Controlled Series Capacitor (TCSC) has immense potential in damping of inter-area power swings and in mitigating the sub-synchronous resonance. In this paper Improved Harmony Search Algorithm (IHSA) has been proposed for coordinated design of multiple PSS and TCSC in order to effectively damp the oscillations. The results obtained by using IHSA on WSCC 3-machine, 9-bus system are found to be superior compared to the results obtained using Bacterial Swarm Optimization (BSO) algorithm. The damping performance of conventional PSS and TCSC controllers is also compared with coordinated design of IHSA based PSS and TCSC on New England 10-machine, 39-bus system over wide range of operating conditions and contingencies. To demonstrate the effectiveness of the proposed technique the results obtained on this test system are also compared with the results obtained with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HSA) and Bacterial Swarm Optimization (BSO).

Wavelet-Based Power System Stabilizer

This paper proposes a wavelet-based power system stabilizer (WPSS) by using both the scaling coefficient energy and the wavelet coefficient energy with border distortions of a one-cycle sliding window. The boundary scaling coefficient energy is used for real-time extraction and compensation of electromechanical oscillations in the synchronous generator, whereas the boundary wavelet coefficient energy is used for the real-time detection of electrical oscillations and for tripping the WPSS at the fault inception time. The performance of the proposed WPSS was assessed in an experimental power system laboratory setup and compared with a conventional power system stabilizer.

Model‐based tuning approach for multi‐band power system stabilisers PSS4B using an improved modal performance index

Multi-band power system stabilisers (MB-PSSs) PSS4B (IEEE standard 421.5-2005) are advanced power system damping controllers that have evident advantages over conventional PSSs in damping low-frequency oscillatory modes. However, finding optimal settings for such controllers is challenging due to the increased complexity of the PSS4B structure. This study describes a methodology for MB-PSS parameter optimisation based on an improved modal performance index as a measure of the controller's stabilising effect. The tuning problem is formulated as a non-linear constrained optimisation search method: proposed modal performance index is chosen as an objective function to be minimised, while properly selected constraints ensure stability of the closed-loop system and robustness of the proposed design. The methodology is demonstrated on a benchmark system that is based on an existing network. Comparative analysis between the MB-PSSs with optimised settings and speed-based PSS1A-type stabilisers designed using the conventional methods show the practicality and effectiveness of the proposed methodology. The implemented approach has an advantage of being scalable and suitable for the model-based tuning of feedback controller of general structure. Additionally, several performance metrics and non-linear simulations in the ElectroMagnetic Transient Program (EMTP) software confirm superior characteristics of PSS4B.

Design and small signal stability enhancement of power system using interval type-2 fuzzy PSS

In this paper the performance analysis of an interval type-2 fuzzy logic controller (IT2 FLC) as a power system stabilizer (PSS) is carried out. The input signals to the controller are considered as speed deviation and acceleration. The application of IT2 FLC as PSS (IT2 FPSS) is considered to improve small signal stability of power system. It is considered for three different benchmark systems such as single-machine infinite-bus (SMIB), two-area four-machine and IEEE ten-machine thirty nine-bus power system. The performance with IT2 FPSS is compared against the performance of the power system without PSS, with conventional PSS (CPSS) and with fuzzy PSS (FPSS). The application of IT2 FPSS is extended to two-area four-machine ten-bus and IEEE New England ten-machine thirty nine-bus power system and speed response comparison is carried out with FPSS. The superiority of performance with IT2 FPSS over type-1 FPSS is validated in terms of ITAE, IAE and ISE.

An adaptive neuro-control approach for multi-machine power systems

• GrHDP approach is investigated for smart grid applications online over time. • Improved damping control performance is obtained via the investigated approach. • Sequential load fluctuations are used to verify the adaptability and robustness. We investigate an adaptive neuro-control approach, namely goal representation heuristic dynamic programming (GrHDP), and study the nonlinear optimal control on the multi-machine power system. Compared with the conventional control approaches, the proposed controller conducts the adaptive learning control and assumes unknown of the power system mathematic model. Besides, the proposed design can provide an adaptive reward signal that guides the power system dynamic performance over time. In this paper, we integrate the novel neuro-controller into the multi-machine power system and provide adaptive supplementary control signals. For fair comparative studies, we include the control performance with the conventional heuristic dynamic programming (HDP) approach under the same conditions. The damping performances with and without the conventional power system stabilizer (PSS) are also presented for comparison. Simulation results verify that the investigated neuro-controller can achieve improved performance in terms of the transient stability and robustness under different fault conditions.

Optimal Power System Stabilizers design via Cuckoo Search algorithm

Abstract Cuckoo Search (CS) algorithm is introduced in this paper for optimal Power System Stabilizers (PSSs) design in a multimachine power system. The PSSs parameter tuning problem is formulated as an optimization problem which is solved by CS Algorithm. An eigenvalues based objective function involving the damping ratio, and the damping factor of the lightly damped electromechanical modes is considered for the PSSs design problem. The performance of the proposed CS based PSSs (CSPSS) has been compared with Genetic Algorithm (GA) based PSSs (GAPSS) and the Conventional PSSs (CPSS) under different operating conditions and disturbances. The results of the developed CSPSS are verified through time domain analysis, eigenvalues and performance indices. Also, the effectiveness of the proposed algorithm in providing good damping characteristics is confirmed.

A Developed Graphical User Interface for Power System Stability and Robustness Studies

This paper present the realization and development of a graphical user interface (GUI) to studied the stability and robustness of power systems (analysis and synthesis), using Conventional Power System Stabilizers (CPSS - realized on PID scheme) or advanced controllers (based on adaptive and robust control), and applied on automatic excitation control of powerful synchronous generators, to improve dynamic performances and robustness. The GUI is a useful average to facilitate stability study of power system with the analysis and synthesis of regulators, and resolution of the compromise: results precision / calculation speed. The obtained Simulation results exploiting our developed GUI realized under MATLAB shown considerable improvements in static and dynamic performances, a great stability and enhancing the robustness of power system, with best precision and minimum operating time. This study was performed for different types of powerful synchronous generators.