Fuzzy Logic Based Power System Research Articles

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.

Design and Analysis of Fuzzy Logic based Power System Stabilizer

Design and Analysis of Fuzzy Logic based Power System Stabilizer

Stability improvement on industrial load using current controlled voltage regulator

In this paper, we considered an industrial load with 33 bus system. This system introduces the modeling of the Current Controlled Voltage Regulator in the load flow calculations for steady-state voltage compensation and loss reduction. Here the performance of the system involves the various ranges of maximum capacity and modeling of this system in its maximum rating of reactive power injection is derived. During this analysis, the proposed fuzzy expert system, generator speed deviation, and its derivative are chosen as input signals to fuzzy logic based power system stabilizer. In this approach centers of membership functions and the parameters of the fuzzy logic controllers have been tuned using a genetic algorithm. Inclusion of GA in tuning fuzzy logic based power system stabilizer will provide good damping and significantly reduces computational time in the design process. Simulation results on a multimachine system subjected to small perturbation and three-phase fault show the effectiveness and robustness of the proposed PSS over a wide range of operating conditions and system configurations.

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.

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

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.

Fuzzy Logic Based Power System Contingency Ranking

Voltage stability is a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures. Modern transmission networks are more heavily loaded than ever before to meet the growing demand. One of the major consequences resulted from such a stressed system is voltage collapse or instability. This paper presents maximum loadability identification of a load bus in a power transmission network. In this study, Fast Voltage Stability Index (FVSI) is utilized as the indicator of the maximum loadability termed as Qmax. In this technique, reactive power loading will be increased gradually at particular load bus until the FVSI reaches close to unity. Therefore, a critical value of FVSI was set as the maximum loadability point. This value ensures the system from entering voltage-collapse region. The main purpose in the maximum loadability assessment is to plan for the maximum allowable load value to avoid voltage collapse; which is important in power system planning risk assessment. The most important task in security analysis is the problem of identifying the critical contingencies from a large list of credible contingencies and ranks them according to their severity. The condition of voltage stability in a power system can be characterized by the use of voltage stability indices. This paper presents fuzzy approach for ranking the contingencies using composite-index based on parallel operated fuzzy inference engine. The Line Flow index (L.F) and bus Voltage Magnitude (VM) of the load buses are expressed in fuzzy set notation. Further, they are evaluated using Fuzzy rules to obtain overall Criticality Index. Contingencies are ranked based on decreasing order of Criticality Index and then provides the comparison of ranking obtained with FVSI method.

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

A New Improved Fuzzy Logic Based Power System Stabilizer

A New Improved Fuzzy Logic Based Power System Stabilizer

Designing Power System Stabilizer for Multimachine Power System Using Neuro-Fuzzy Algorithm

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.

Speaker-Independent Malay Syllable Recognition Using Singular and Modular Neural Networks

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.

POWER SYSTEM STABILIZATION USING SWARM TUNED FUZZY CONTROLLER

This paper proposes a swarm optimized fuzzy logic based power system stabilizer (SFLPSS). The fuzzy logic stabilizer membership functions parameters, inputs and outputs gains and fuzzy rules are tuned and optimized using particle swarm optimization (PSO) technique. Optimization parameters were subject to realistic constraint. The optimization is done using a seventh order nonlinear model of a single synchronous machine connected to infinite bus bar. A Guided simulation technique using stability limits check is used to accelerate the PSO algorithm search for optimized parameters. Optimization results in reduction of fuzzy rules. Transient tests of the optimized controller performance showed better performance over conventional controllers.

00/01936 Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm

00/01936 Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm

Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm

The paper presents a procedure for application of Fuzzy logic Power System Stabilizer (FPSS) for stability enhancement of a multimachine power system. The location of Power System Stabilizer (PSS) is determined using critical modes and participation factors for different operating conditions. A simple configuration is chosen for FPSS with a speed deviation of synchronous generator and its derivative as input signals. The parameters of the stabilizers are tuned through simulation of non-linear model of power system under chosen disturbance using Crowding Genetic Algorithm (CGA) to minimize a Root Mean Square Deviation (RMSD) index of the concerned state variable which maximizes the damping of the critical mode. Results obtained from a two area, five generator power system indicate the improved performance of FPSS over conventional PSS.

A Fuzzy Logic Based PSS Using a Standardized Rule Table

To achieve better performance for the controlled system, the rule table of a fuzzy logic based controller is often determined by trial and error. To simplify this time-consuming task, a standardized rule table that can be used in a fuzzy logic control design procedure is developed in this paper. To demonstrate its applicability, the design technique proposed in this paper is employed to design a fuzzy logic based power system stabilizer. Details of the design procedure and results of performance studies with the proposed stabilizer are given in the paper.

Design of a robust power system stabilizer using fuzzy logic for a multi-machine power system

This paper presents a design procedure for a fuzzy logic based power system stabilizer (FPSS) and investigates the robustness of the FPSS for a multi-machine power system. Speed deviation of synchronous generator and its derivative are chosen as the input signals to the FPSS. A two area, five generator power system is used to illustrate the robustness of the FPSS. A normalized sum-squared deviation (NSSD) index is used for designing the FPSS and demonstrating its robustness. Nonlinear simulation tests for different disturbances and their results are discussed.

Performance of a Fuzzy Logic Based PSS in a Multi-Machine Power System Environment

Effectiveness of the fuzzy logic based power system stabilizer in a multi-machine power system environment is investigated in this paper. The power system used to study the performance of the stabilizer exhibits multi-mode oscillation phenomena. Machine speed deviation and accelerating power as the plant's output are used as the inputs to the stabilizer. Results of simulation studies for different operating conditions and disturbances are given in the paper.

Implementation of a fuzzy logic PSS using a micro-controller and experimental test results

Implementation of a fuzzy logic based power system stabilizer using the general purpose low cost Intel 8051FA microcontroller is described in this paper. Results of extensive on-line tests performed for a variety of disturbances and operating conditions are presented. These results amply demonstrate the effectiveness of the fuzzy logic based stabilizer.

A fuzzy logic based power system stabilizer with learning ability

A fuzzy logic-based power system stabilizer (PSS) with learning ability is proposed in this paper. The proposed PSS employs a multilayer adaptive network. The network is trained directly from the input and the output of the generating unit. The algorithm combines the advantages of artificial neural networks (ANNs) and fuzzy logic control (FLC) schemes. Studies show that the proposed adaptive network-based fuzzy logic PSS (ANF PSS) can provide good damping of power systems over a wide range of operating conditions and improve the dynamic performance of the power system.

Application of fuzzy logic stabilisers in a multimachine power system environment

Application of fuzzy logic based power system stabilisers (FLPSS) in a multimachine environment is described. A five-machine power system representing two generation areas is used. The proposed FLPSS uses machine speed deviation and accelerating power as the inputs. The performance of the FLPSS when the system exhibits multimode oscillation phenomenon is illustrated. Simulation tests and results for different operating conditions and disturbances are discussed.