Fuzzy Power System Stabilizer Research Articles

Improvement of an AC microgrid system’s stability by using a fuzzy logic-based PSS controller

This research article presents the low-frequency oscillation damping control of an AC Microgrid. It is integrated with four distributed generation units in which two DGs are renewable energy source based solar PV and wind energy using DFIG and the other two DGs are conventional synchronous generator-based hydro and diesel generators. There is insufficient generation through renewable-based DG then a diesel generator is employed as an emergency unit to fulfil the requirements and maintain and control the deviation of the frequency of the system. The use of renewable-based DG affected the system's dynamic stability and the characteristics of an integrated microgrid differ from conventional sources of generation. This investigation explores the impression of the deployment of multiple forms of the power oscillation damping (POD) controllers to distributed generation sources of grid forming AC Microgrid. The main various types of POD controllers are conventional lead-lag PSSs, MBPSS-4B, and proposed robust fuzzy logic PSS (FLPSS) controllers are implemented on distributed generation units of AC Microgrid for the elimination of low-frequency oscillation. Low oscillation frequencies between 0.1 and 2 Hz are the focus of this work. The system's damping ratios and stability margins because of MG integration are observed using eigenvalues analysis. The results of the simulation test demonstrate the accomplishment of the robust fuzzy logic PSS controller regarding conventional lead-lag PSSs and the MBPSS-4B controller during circumstances of fault.

Impact and Integration of Electric vehicles on renewable energy based Microgrid: Frequency profile improvement by a-SCA optimized FO-Fuzzy PSS approach

The modelling of an electric vehicle along with its integration and impact over a renewable energy based microgrid topology is well addressed in this manuscript. The frequent charging and discharging of the electric vehicle makes an oscillation over grid frequency. The performance especially frequency of an islanded AC microgrid is also affected seriously under the actions of different uncertainties like load dynamics, wind fluctuation in wind plant, solar intensity variation of PV plant etc. In order to maintain standard frequency, this research work aims to regulate the net power generation of the system in response to total demand. To monitor net generation, this work has intended a fractional order fuzzy power system stabilizer (FO-Fuzzy PSS) control scheme in several dynamic situations. The proposed FO-Fuzzy PSS control scheme acts as most potential candidate to pertain stability in system frequency in above discussed disturbances. The controller gains are tuned optimally with suggesting an advanced- Sine Cosine Algorithm (a-SCA) under different conditions. The performance of the optimal FO- Fuzzy PSS controller is compared over standard fuzzy controller and PID controller in regard to frequency regulation of microgrid system. It is observed that proposed FO-Fuzzy PSS control scheme has the credential to reduce settling time of ΔF1 (area1 microgrid frequency) by 98.60% and 250.82% over fuzzy controller & PID controller correspondingly. Further, the dynamic optimal performance of the proposed a-SCA is compared over original SCA and PSO techniques to justify its superiority.

Chaotic Harris hawks optimisation based fuzzy lead lag TCSC and PSS with coordinated control design for enhancement of power system transient stability

Chaotic Harris hawks optimisation based fuzzy lead lag TCSC and PSS with coordinated control design for enhancement of power system transient stability

Chaotic Harris hawks optimisation based fuzzy lead lag TCSC and PSS with coordinated control design for enhancement of power system transient stability

This paper investigated the application of Chaotic Harris Hawks optimisation (CHHO) technique for the tuning of a coordinated control of fuzzy lead lag based TCSC controller with fuzzy based PSS power system. The eigenvalues and simulation results of proposed CHHO optimised TCSC controller are presented and compared with a coordinated control of lead lag TCSC controller with PSO, DE and GSA optimised lead lag controller under various cases of operating conditions and disturbances in SMIB power system. The CHHO optimised of proposed fuzzy coordinated controller is compared with CHHO based lead lag TCSC coordinated control of same power system to check the effectiveness and robustness analysis. Finally, the proposed design approach is extended to multi-machine test model system to demonstrate the coordinated control of fuzzy lead lag TCSC damping controller with fuzzy power system stabilises to damp out oscillations in power system to improve transient stability performances.

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.

Improvement of Dynamic Stability of a Single Machine Infinite-Bus Power System using MPC based Power System Stabilizer

Abstract— Power system stabilizers (PSSs) are used to enhance the damping during low frequency oscillations. This paper presents a study of power system stabilizer using fuzzy logic to enhance the stability of single machine infinite bus system. In this paper the problem of conventional power system stabilizer for stability enhancement is presented which is traditionally used as well as, an effective techniques using Artificial Intelligence (AI) based on fuzzy logic and Model Predictive Control (MPC) is used in designing the control system for PSS in order to achieve recognized improvement in Dynamic Stability. In the last few years fuzzy logic and MPC are used in power system applications as a powerful tool and shows recognized improvement in the stability performance This paper presents a solution for enhancing the improvement in the performance of single machine infinite bus system with fuzzy power system stabilizer of triangular membership function. Speed deviation (w) and acceleration are taken as an input variable. The performance of conventional, fuzzy based power system stabilizer with triangular membership function and MPC responses are studied and compared with conventional lead-lag compensator. The simulations are implemented using MATLAB - SIMULINK as a simulation program tool.

Simultaneous design of fuzzy PSS and fuzzy STATCOM controllers for power system stability enhancement

The low frequency oscillations have always been the main problem of power system and can lead to power angle instability, limiting the maximum power to be transmitted on tie-lines and system separation. For boosting power system stability limits, the most effectiveness way is to install supplementary excitation control, power system stabilizer (PSS) to add a supplementary feedback stabilizing signal into the automatic voltage regulator (AVR). This article investigates the coordination and optimization of fuzzy controllers for designing PSS and STATCOM controllers for more attenuation of power system fluctuations. The designed fuzzy controller replaces the STATCOM AC voltage regulator. Moreover, for more damping a fuzzy power system stabilizer (FPSS) is placed on all machines. Coordination between Fuzzy Based STATCOM (FSTATCOM) and FPSS is achieved by Self-Adaptive Learning Bat Algorithm (SALBA) in two stages. At first, scaling factors and then fuzzy sets of membership functions (MFs) will be tuned based on a performance index. To indicate the effectiveness of the proposed scheme, the coordinated optimized FPSS and FSTATCOM are compared with conventional design approaches like conventional PSS (CPSS) and proportional-integral controller based STATCOM (PISTATCOM). The simulations clearly demonstrate the effectiveness of the coordinated fuzzy controllers in terms of transient and dynamic stability.

Efficient Self-Tuned Fuzzy Logic Based Power System Stabilizer

A mechanism for efficient self-tuning of a fuzzy logic-based PSS in real-time is presented. The proposed controller with a self-tuning mechanism can reduce low-frequency oscillations regardless of magnitude or type of disturbance, whether sudden or gradual. It is not necessary to set the initialization or learning factor for each disturbance and its implementation is simple. Speed deviation and its derivative are used as fuzzy controller inputs. The main idea, based on the properties of the conventional PID controller, is to use a fuzzy controller similar to a PID controller but for the nonlinear power system. Since the objective is implementation on a physical system, nonlinearity without any simplification of the system is very important. Therefore, in this mechanism, the full order machine model is considered. The optimal performance is obtained by determining in real-time the appropriate gains for each input. Tests for a wide range of disturbances show the robustness of the controller. The proposed approach has fewer fuzzy rules than similar methods. Therefore, its hardware implementation can be simpler and will require less computation time. Very good damping of all types of disturbances is a prominent feature of this method.

Influence of Fuzzy Power System Stabilizer using Different Membership Functions for Single and Multi-machine

Influence of Fuzzy Power System Stabilizer using Different Membership Functions for Single and Multi-machine

An optimised Interval type-2 fuzzy PID-based PSS for stability improvement in solar-PV integrated power system considering uncertainties

This paper presents a robust Interval type-2 Fuzzy Proportional Integral Derivative (IT2FPID)-based Power System Stabiliser (PSS) to lessen low-frequency oscillations (LFOs) in the power system with Solar Photovoltaic (SPV) systems. Uncertainties in the power system do not allow the PSS to function at its maximum capacity and also have adverse impacts on dynamic stability. The proposed ITFPID-PSS can easily handle the uncertainties of load and PV systems in Single Machine Infinite Bus (SMIB) and Multimachine Power System (MMPS) due to its unique shape of its membership function. The gains of the proposed IT2FPID-PSS are optimised using Jaya algorithm. The performance of the proposed controller is evaluated under different operating conditions and also compared with the conventional PSS. Both graphical and comparative investigations suggest the superiority of the proposed Jaya algorithm-optimised IT2FPID-PSS over CSA-optimised IT2FPID-PSS and FA-optimised IT2FPID-PSS under various operating conditions and load disturbances.

An intelligence technique-based control model for power system stabiliser

In the power system, voltage instability is one of the important issues and it may cause voltage sag, voltage swell, change in load and generation of harmonics. To tackle all these problems, the transmission power system makes use of an intelligent control model to improve the stability of power system. In this paper, a new adaptive neuro fuzzy inference system (ANFIS) based power system stabiliser (PSS) for the enhancement of voltage stability in power systems is proposed. A hybrid learning algorithm, which combines the least squares method and the back propagation algorithm, is used to train the ANFIS. The performance of the power system by using fuzzy based PSS is about 60.1% when compared to that of the conventional PSS. To evaluate the effectiveness of the proposed technique the performance of the proposed technique was compared with the results obtained by using fuzzy PSS model and its performance was analysed. Simulation results described in the paper demonstrate that the adaptive neuro-fuzzy based PSS can give 33.43% of improvement in voltage stability when compared to that of fuzzy based PSS over a wide range of operating conditions.

A Novel Fuzzy Rule Matrix Design for Fuzzy Logic-based Power System Stabilizer

In this paper, fuzzy logic-based power system stabilizer (FPSS) is designed to have effective damping. As to achieve impressive performance of a controlled plant, the rule base/fuzzy rule matrix (FRM) of a fuzzy logic controller (FLC) is designed by trial–error method, which is a time-consuming process. In this paper, a systematic procedure is given to design FRM for effective damping of single-machine infinite-bus (SMIB) and two-area four-machine ten-bus power system. To design the novel FRM, the existing rule tables, proposed by different researchers, are tested with SMIB system, and empirical relationships have been drawn. The response validity and rule justification is carried out using linguistic phase-plane trajectory method. Finally, the contribution to design FRM is made to get effective damping for SMIB as well as a multi-machine system. The effectiveness of the FPSS based on the proposed FRM over a wide range of operating conditions on SMIB system and the comparison of system response without PSS, with Conventional PSS, and with FPSS is carried out. Similarly, the multimachine power system is considered without PSS and with FPSS, and performance comparison is carried out. The response of FPSS with proposed FRM enables to show the effective damping of system oscillations.

A Robust Control with the Combination of Fuzzy and SMC to Stabilize the Power System

<p>Common power system stabilizer (CPSS), fuzzy power system stabilizer (FPSS) and sliding mode controller (SMC) are common controllers which are used in controlling single machine infinite bus (SMIB) power systems. Each of these controllers has disadvantages. CPSS is not robust enough to stabilize the power system perfectly. SMC is more robust than CPSS but in the presence of big uncertainties it is unable to stabilize power system. FPSS is enough robust in the presence of big uncertainties, but it causes chattering when high switching gain is needed. The goal of this paper is to present a robust controller for a single machine infinite bus (SMIB). The proposed controller is a direct fuzzy controller assisted with a sliding mode controller. The simulation shows clear positive effect and validity of the method in convergence, time and accuracy.</p>

Fuzzy-PSS and fuzzy neural network non-linear PI controller-based SSSC for damping inter-area oscillations

In this paper, a new approach is recommended for damping out power system oscillations. In this approach, a new fuzzy neural proportional–integral (PI) controller (FNPIC) based static synchronous series compensator (SSSC) and a fuzzy-power system stabilizer (fuzzy-PSS) with a new structure are simultaneously employed. Adaptive learning rates based on the Lyapunov stability theory to enhance the convergence speed of the proposed controller are obtained. In the structure of fuzzy-PSS, a pattern search algorithm is used to adjust four gains. A two-area four-machine power system and a three-area, three-machine power system are employed to investigate the efficiency of the proposed method. Simulations results confirm the capabilities of proposed controller in suppressing the power system oscillations.

Design of optimal input–output scaling factors based fuzzy PSS using bat algorithm

In this article, a fuzzy logic based power system stabilizer (FPSS) is designed by tuning its input–output scaling factors. Two input signals to FPSS are considered as change of speed and change in power, and the output signal is considered as a correcting voltage signal. The normalizing factors of these signals are considered as the optimization problem with minimization of integral of square error in single-machine and multi-machine power systems. These factors are optimally determined with bat algorithm (BA) and considered as scaling factors of FPSS. The performance of power system with such a designed BA based FPSS (BA-FPSS) is compared to that of response with FPSS, Harmony Search Algorithm based FPSS (HSA-FPSS) and Particle Swarm Optimization based FPSS (PSO-FPSS). The systems considered are single-machine connected to infinite-bus, two-area 4-machine 10-bus and IEEE New England 10-machine 39-bus power systems for evaluating the performance of BA-FPSS. The comparison is carried out in terms of the integral of time-weighted absolute error (ITAE), integral of absolute error (IAE) and integral of square error (ISE) of speed response for systems with FPSS, HSA-FPSS and BA-FPSS. The superior performance of systems with BA-FPSS is established considering eight plant conditions of each system, which represents the wide range of operating conditions.

WIDE-AREA BASED ON COORDINATED TUNING OF FUZZY PSS AND FACTS CONTROLLER IN MULTI-MACHINE ENVIRONMENT

In this paper coordination of fuzzy power system stabilizer (FPSS) and flexible ac transmission systems (FACTS) have been considered in a multi-machine power system. The proposed model, has been applied for a wide-area power system. The proposed FPSS presented with local, nonlinear feedbacks, and the corresponding control synthesis conditions are given in terms of solutions to a set of linear matrix inequalities (LMIs). For this model, in fuzzy control synthesis, the new proposed control design method is based on fewer fuzzy rules and less computational burden. Also, the parameters of FACTS controller have been evaluated by improved honey bee mating optimization (IHBMO). The effectiveness of the proposed method has been applied over two case studies of single-machine infinite-bus (SMIB) and two areas four ma chine (TAFM) Kundur’s power system. The obtained results demonstrate the superiority of proposed strategy.

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.

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.

Multi-stage Fuzzy Power System Stabilizer based on Modified Shuffled Frog Leaping Algorithm

This paper presents a new strategy based on Multi-stage Fuzzy (MSF) PID controller for damping Power System Stabilizer (PSS) in multi-machine environment using Modified Shuffled Frog Leaping (MSFL) algorithm. The proposed technique is a new meta-heuristic algorithm which is inspired by mating procedure of the honey bee. Actually, the mentioned algorithm is used recently in power systems which demonstrate the good reflex of this algorithm. Also, finding the parameters of PID controller in power system has direct effect for damping oscillation. Hence, to reduce the design effort and find a better fuzzy system control, the parameters of proposed controller is obtained by MSFL that leads to design controller with simple structure that is easy to implement. The effectiveness of the proposed technique is applied to Single machine connected to Infinite Bus (SMIB) and IEEE 3-9 bus power system. The proposed technique is compared with other techniques through ITAE and FD.

Multi-stage Fuzzy Power System Stabilizer based on Modified Shuffled Frog Leaping Algorithm

Multi-stage Fuzzy Power System Stabilizer based on Modified Shuffled Frog Leaping Algorithm