Fuzzy Logic Power System Stabilizer Research Articles

Stabilizing multimachine power systems with fuzzy logic using artificial bee colonies

Over the past few years, fuzzy logic systems have gained popularity due to their superiority over classical controllers when it comes to enhancing the transient stability of power systems. In this paper, a Fuzzy Logic Power System Stabilizer (FLPSS) is designed to damp local and inter-area oscillations following disturbances through the use of an Artificial Bee Colony Optimization Algorithm (ABC). The designed FLPSS is expected to significantly increase the robustness of power systems and ultimately improve the quality of power supply to end-users. This test system consists of two areas with four machines and eleven buses, with the purpose of evaluating the performance of the ABC-FLPSS under a variety of disturbances and loads. In order to optimize the scaling factors of FLPSSs, the Integral Squared Error (ISE) of rotor speed deviation is formulated as an objective function. Evaluation of the proposed controller involves simulating the test system under different conditions. These conditions range from small perturbations, such as changes in one of the system parameters, to large changes, such as removing a main transmission line, to determine its effectiveness. A comparison of ABC-FLPSS with FLPSS and Conventional Power System Stabilizer (CPSS) shows that the ABC-FLPSS controller is superior to FLPSS and CPSS.

A Grey Wolf Optimizer algorithm based fuzzy logic power system stabilizer for single machine infinite bus system

Low-frequency power oscillations in power systems have always been a serious risk for a stable power system. A fuzzy logic power system stabilizer (FLPSS) is proposed to mitigate system oscillation problems. Aimed at parameter configuration and rule setting of FLPSS, Grey Wolf Optimizer (GWO) based FLPSS is utilized to achieve quicker settling time and improve the damping oscillation effectiveness. Comparative studies between the proposed GWO-based FLPSS and conventional stabilizers are performed on a single-machine infinite bus system(SMIBS). The simulation results demonstrate the GWO-based FLPSS can better dampen out low-frequency oscillations and maintain the electricity network stability.

Синтез системного стабилизатора с применением методов нечеткой логики и нейронной сети

Power systems are large non-linear systems that are often subject to low frequency electromechanical oscillations with a frequency of 0.5–2.5 Hz. Power system stabilizers (PSS) are commonly used as effective and economically efficient means to dampen electromechanical oscillations of generators and increase the stability of power systems. PSS can increase the power transmission stability limits by adding a stabilizing signal through the channels of the automatic excitation control system. The article presents the results of training a neural network based on which a fuzzy logic PSS is obtained for increasing the stability of electric power systems. The synchronous generator rotor speed deviation and acceleration were taken as input data for the fuzzy logic controller. These variables have a significant effect on damping the rotor's electromechanical oscillations. The characteristics of the power system equipped with the proposed fuzzy logic based PSS are compared with its characteristics with a PSS with non-optimized parameters and without a PSS.

The integrated control strategy for interval Type-2 fuzzy logic power system stabilizer (IT2FLPSS) and compact digital fuzzy automatic voltage regulator (CDF-AVR) in electrical power system

The integrated control strategy for interval Type-2 fuzzy logic power system stabilizer (IT2FLPSS) and compact digital fuzzy automatic voltage regulator (CDF-AVR) in electrical power system

Design of Type-2 Fuzzy Logic Power System Stabilizer Using Limit cycle approach

Power system is subjected to wide range of operating conditions. Heavily loaded power systems are subjected to Hopf bifurcations resulting in oscillatory instability. A power system shifts to the dynamic instability region encountered by unstable limit cycles, this result in increase of oscillatory behaviour of power system. Many of the authors suggested the theories like Poincare-Bendixson theory, bifurcation theory, eigenvalue theory and shooting methods for finding dynamic stability margin. Small signal stability focuses on eigenvalue computation at a given operating point. The onset of instability is obtained by finding Hopf bifurcations associated with a pair of imaginary eigenvalues using eigenvalue analysis. Computation of these HBs is a tedious and complex task in traditional approach. In this paper, a novel computational algorithm is proposed to identify the loading conditions resulting in these limit cycles, which are associated with a pair of imaginary eigenvalues, using genetic algorithm for single machine infinite bus (SMIB) and multi machine power system (MMPS) models. The derived loading conditions are used to systematically design a robust type-2 fuzzy logic power system stabiliser. The efficacy of the proposed controller is tested for linear and nonlinear models of power system under various operating conditions.

Selection of Membership Functions Based on Fuzzy Rules to Design an Efficient Power System Stabilizer

This paper presents an evaluation of membership functions on a single-machine infinite-bus and two-area four-machine ten-bus power system with power system stabilizers (PSSs). The PSS is added to an excitation system to enhance the damping during low-frequency oscillations. In this paper, the system is analysed for fuzzy logic power system stabilizer (FPSS) with different membership functions (MFs). The speed deviation ( $$\Delta \omega$$ ) and acceleration ( $$\Delta \dot{\omega }$$ ) of the rotor of a synchronous generator are taken as the input to the fuzzy logic controller to improve small signal stability by enhancing damping. The effect of these variables on damping at the generator shaft mechanical oscillation is very significant. The stabilizing signals were computed using the different fuzzy membership functions in the Mamdani inference system. The general membership functions under consideration are triangular, trapezoidal, Gaussian, bell, sigmoid and polynomial types. The performance of the fuzzy logic PSS with different membership functions is compared to get best-suited MF to design an FPSS. The best-performing MF is found based on simulation study with both power systems and with varying no. of linguistic variables as well. It is found that, If the number of linguistic variables is 3 or 5, the preferred best-suited membership function appears as the Gaussian type, while with increased linguistic variables as 7 or above, then the triangular MF is preferable as the performance is better in comparison with Gaussian MF.

Improvement of Power System Dynamic Stability Based on Fuzzy Logic Power System Stabilizer (FLPSS)

Generally this project is to improve the dynamic power system stability using fuzzy logic power system stabilizer (FLPSS) which applied to the excitation system. This research is started by electric power system mathematic modelling (state variable equation) and block diagram then set membership function of fuzzy logic power system stabilizer (FLPSS). Block diagram model (plant system) is formed from state variable equation. The plant is controlled by fuzzy logic power system stabilizer (FLPSS) which its input and output from the rotor speed and to excitation system, respectively. To observe the oscillation of dynamic power system stability, the electrical power is varied ± 0.1 pu (positive and negative value indicate an increasing and decreasing electrical power, respectively). The result shows that using FLPSS, the oscillation of dynamic power system can be improved. The overshoot of electric power and rotor speed change oscillation after the disturbance is smaller than the conventional, and also the time to reach the steady state is faster.

Comparing the Performance of UPFC Damping Controller on Damping Low Frequency Oscillations

This paper compares the performance of UPFC damping controller (, and ) to damp Low Frequency Oscillations (LFO) in power system equipped with UPFC based on Fuzzy Logic Power System Stabilizer (UPFC based FLPSS). The power system model was developed using linearized model of Phillips-Heffron Single Machine Infinite Bus (SMIB) and simulated in Matlab Simulink. The ability of each controller to damp LFO present in the rotor speed was monitored when the system being perturbed by small disturbances. The results obtained shown that UPFC controller had better performance to damp LFO compared to the other UPFC damping controllers as it had the lowest overshoot and less settling time.

Optimal Tuning of Fuzzy Logic Power System Stabilizer Using Harmony Search Algorithm

In this paper, the design of fuzzy logic power system stabilizer (FPSS) is carried out using a harmony search algorithm (HSA) to optimize the input–output scaling factors of the fuzzy logic controller. The optimization problem is considered minimization of integral square error as an objective function with single-machine and multimachine power system. The performance of the HSA optimized FPSS with both systems is compared that of with robust FPSS; HSA tuned input scaling factors of FPSS, and particle swarm optimization tuned input–output FPSS for a wide range of operating conditions. The speed response performance for both systems is compared in terms of performance indices, and superiority of the proposed HSFPSS is validated.

Improved Step Response of Power System Stabilizer using Fuzzy Logic Controller

As every power system is constantly being subjected to disturbances, we should see that these disturbances do not make the system unstable. Therefor additional signals derived from speed deviation, excitation deviation and accelerating power are injected into voltage regulators. The device to provide these signals is referred as power system stabilizer. The use of power system stabilizers has become very common in operation of large electric power systems. The conventional PSS which uses lead-lag compensation, where gain settings designed for specific operating conditions, is giving poor performance under different loading conditions. Therefore, it is very difficult to design a stabilizer that could present good performance in all operating points of electric power systems. In an attempt to cover a wide range of operating conditions, Fuzzy logic control has been suggested as a possible solution to overcome this problem. In this paper, a systematic approach to fuzzy logic control design is proposed. The study of fuzzy logic power system stabilizer for stability enhancement of a single machine infinite bus system is presented. In order to accomplish the stability enhancement, speed deviation and acceleration of the rotor synchronous generator are taken as the inputs to the fuzzy logic controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using the fuzzy membership function depending on these variables. The performance of the system with fuzzy logic based power system stabilizer is compared with the system having conventional power system stabilizer and system without power system stabilizer

Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm

In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance by uncertainty of membership function especially when we have to confront with less expert knowledge or unpredicted external disturbances. The corresponding parameters and rule base of type-2 fuzzy logic power system stabilizer are optimally tuned by using differential evolution algorithm for multi-machine power system. Through simulation under different operational conditions, the results demonstrate the effectiveness of the proposed approach for damping the power system electromechanical oscillations.

Dynamic Stability Enhancement of Power System Using Fuzzy Power System Stabilizer Under Different Loading Conditions

The power system is dynamic in nature and is constantly being subjected to disturbances. It enters into dynamic instability when there is an imbalance between generation and varying load demand which calls for use of Power System Stabilizer (PSS). PSS is a device which provides additional signal to the voltage regulator derived from speed deviation, excitation deviation and accelerating power for damping critical oscillations. The PSS used should be capable to produce appropriate stabilizing signals against a wide range of operating conditions and disturbances. For this purpose, a PSS based on fuzzy logic control under multi-operating conditions is proposed in this paper. The performance of Fuzzy Logic based PSS(FLPSS) applied to Single Machine Infinite Bus (SMIB) system is studied for three different operating conditions; nominal load, heavy load and fault condition in transmission line. For Fuzzy PSS, speed deviation and acceleration are taken as input. The system is simulated in SIMULINK platform and its dynamic response is analyzed for system without PSS and with PSS. The results are compared for system with Conventional PSS and Fuzzy Logic PSS.

Damping of low‐inertia machine oscillations using Takagi‐Sugeno fuzzy stabiliser tuned by genetic algorithm optimisation to improve system stability

The implementation of distributed generation (DG) in a power network may introduce undesirable transients or network oscillations in power networks due to low or no inertia. These undesirable transients and oscillations may be dampened through the use of power system stabiliser (PSS), if properly designed. In this study, an intelligent PSS comprising of Takagi-Sugeno (TS) fuzzy-logic control and genetic algorithm optimisation is proposed to effectively dampen these oscillations. Eigenstudy and participation factor analysis have been carried out to determine critical issues relating to angle instability such that the intelligent PSS can be designed accordingly. The proposed fuzzy-logic stabiliser is tested on an Australian power network using network data provided by an industry participant. To demonstrate the effectiveness of the proposed fuzzy-logic PSS, a number of disturbances have been simulated and the response of the interconnected DG units of rotary type is assessed in terms of rotor angle and rotor speed. The results demonstrate that the proposed fuzzy-logic controller substantially improves the performance of the network transients with DG by effectively damping local oscillations in the machine rotor angle and machine rotor speed.

Performance Of Power System Stabilizerusing Fuzzy Logic Controller

Power system stabilizers (PSS) must be capable of providing appropriate stabilization signals over a broad range of operating conditions and disturbances. Traditional PSS rely on robust linear design methods. In an attempt to cover a wide range of operating conditions, expert or rule based controllers have been proposed. Recently, fuzzy logic as a novel robust control design method has shown promising results. In this paper a fuzzy logic based power system stabilizer for stability enhancement of a two-area four machine system are designed. In order to accomplish the stability enhancement, speed deviation (Δω) and active power deviation (ΔP) of the rotor synchronous generator were taken as the inputs to the fuzzy logic controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using fuzzy membership function depending on these variables. The performance of the system with fuzzy logic PSS is compared with the conventional PSS and the system without PSS.

Design of Harmony Search Algorithm Based Tuned Fuzzy Logic Power System Stabilizer

In this paper, a robust Harmony Search Algorithm tune Type-1 fuzzy logic power system stabilizer (HSFPSS) is designed. The fuzzy logic controller lacks the mathematical reasoning & the performance is reviewed by transient response of the closed-loop system. A small-signal model of the fuzzy logic power system stabilizer (FPSS) is derived to optimize the scaling factors using Harmony Search Algorithm (HSA). The derived such a small signal model of FPSS is proven to be a Proportional Derivative controller. The parameters of the PD controller are considered as the normalized factors of the FPSS & are tuned using HSA. The simulations over the wide range of operating conditions of the power system are carried out to show the superiority of the proposed controller.

Performance Assessment of Fuzzy Logic Power System Stabilizer on North Benghazi Power Plant

Fuzzy logic design has been implemented online to tune the power system stabilizer gain (KPSS). To assess the performance of the proposed technique, Benghazi North Power Plant (BNPP), at eastern Libyan network, has been utilized as a power system stabilizer (PSS) benchmark. The design considers different operating conditions and large disturbance. A selection of fuzzy rules is derived by means of system output power to tune KPSS, whereas Particle Swarm Optimization technique (PSO) is exploited to calculate the PSS parameters offline according to real-time measurements of the considered plant. Several simulation scenarios have been conducted to show the effectiveness of the proposed PSS in damping of local and interarea modes of oscillation of one-machine infinite-bus system. The study also contains comparison between the proposed technique and conventional PSS (CPSS).

Robust fuzzy logic power system stabilizer based on evolution and learning

A robust fuzzy logic power system stabilizer (FLPSS) based on evolution and learning is proposed in this paper. A hybrid algorithm that combines learning and evolution is developed whereby each one complements other’s strength. Parameters of FLPSS are encoded in chromosome (individual) of genetic algorithm (GA) population. Population of FLPSS in GA learns to stabilize electromechanical oscillations in power system at an operating point, as the best fitness becomes large steady value during successive generations. Operating region of FLPSS is enlarged by learning more operating points over the operating domain. Best FLPSS drawn from last generation is saved as designed FLPSS. Effectiveness of the proposed method is validated on a single machine infinite bus (SMIB) power system. Promising optimal stabilizing performance with designed FLPSS for considered power system is obtained at wide range of operating points.

Enhancement of Power System Stability Using Fuzzy Logic Controller

This Dissertation includes work on the development of a fuzzy logic power system stabilizer to enhance the damping of generator oscillations In order to accomplish a stability enhancement. Speed deviation (Am) and acceleration (Aw) of the rotor synchronous generator were taken as the input to the fuzzy logic controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using the fuzzy membership function depending on these variables. The performance of the fuzzy logic power system stabilizer was compared with the conventional power system stabilizer and without power system stabilizer. To achieve good damping characteristics over a wide range of operating conditions, speed deviation and acceleration of a synchronous machine are chosen as the input. Signal to the stabilizers. The stabilizing signal is determined from certain rules for rule-based power system stabilizer. For fuzzy logic based power system stabilizer, the supplementary stabilizing signal is determined according to the fuzzy membership function depending on the speed and acceleration states of the generator. The simulation result shows that the proposed fuzzy logic based power system stabilizer is superior to rule-based stabilizer due to its lower computation burden and robust performance. DOI: http://dx.doi.org/10.11591/ijpeds.v2i4.2127

Proportional plus derivative output feedback based fuzzy logic power system stabiliser

Most of the design of a fuzzy logic power system stabiliser (FLPSS) relies on researchers’ experience, or trial and error tuning. One may use searching algorithms like genetic algorithms to determine the parameters but this remains time-consuming. This paper proposes an approach to the design of a FLPSS based on proportional plus derivative output feedback PSS (PDPSS). The proposed approach is effective and efficient. First a proportional plus derivative output feedback PDPSS is designed, and then this PDPSS is converted into FLPSS. Computer simulations of a multi-machine power system have justified the feasibility, effectiveness and efficiency of the proposed approach.

Digital Simulation of Reduced Rule Fuzzy Logic Power System Stabilizer for Analysis of Power System Stability Enhancement

Digital Simulation of Reduced Rule Fuzzy Logic Power System Stabilizer for Analysis of Power System Stability Enhancement