Advanced PID type fuzzy logic power system stabilizer

An advanced fuzzy logic control scheme has been proposed for a microcomputer based power system stabilizer to enhance the overall stability of power systems. The proposed control scheme utilizes the PID information of the generator speed. The input signal to the stabilizer is the real power output of a study unit. Simulations show the effectiveness of the advanced fuzzy logic control scheme     

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     

Implementation of a fuzzy logic PSS using a micro-controller andexperimental 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     

Real time control of micro-machine system using micro-computerbased fuzzy logic power system stabilizer

A microcomputer based fuzzy logic power system stabilizer is applied to a micro-machine system to investigate its efficiency in real time control. The stabilizing signal is determined by using measured speed or real power signals at every sampling time to damp the system oscillations. The results show the proposed stabilizer improves the system damping effectively subject to various types of disturbances     

Implementation and laboratory test results for an adaptive powersystem stabilizer based on linear optimal control

Implementation of an adaptive power system stabilizer (PSS) based on linear optimal control is described. The generator is identified in real time, and a special third-order discrete Riccati equation is solved in each sample interval. Because the output of the generator is fed back directly, the controller can track the system very fast. Experimental studies on a physical model of a micromachine alternator connected to a constant voltage bus through a transmission line are reported. The PSS was implemented using a multiprocessor architecture employing separate processors for identification, control, and man-machine interface. The various parameters are tuned to obtain the best performance under various disturbances. Test results show that the proposed PSS is very effective in damping out the system oscillation     

A fuzzy logic based stabilizer for a synchronous machine

The application of a fuzzy logic controller to improve the stability of electric power systems is presented. The stabilizing signal is computed using the standard fuzzy membership function depending on the speed acceleration state of the generator in the phase plane. The required measurement is the speed deviation over two samples. The effectiveness of the proposed stabilizer is demonstrated by simulation studies for different operating conditions and disturbances     

Design and analysis of an adaptive fuzzy power system stabilizer

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 wider range of operating conditions, expert or rule-based controllers have also been proposed. Fuzzy logic as a novel robust control design method has shown promising results. The emphasis in fuzzy control design centers around uncertainties in system parameters and operating conditions. Such an emphasis is of particular relevance as the difficulty of accurately modelling the connected generation is expected to increase under power industry deregulation. Fuzzy logic controllers are based on empirical control rules. In this paper, a systematic approach to fuzzy logic control design is proposed. Implementation for a specific machine requires specification of performance criteria. This performance criteria translates into three controller parameters which can be calculated off-line or computed in real-time in response to system changes. The robustness of the controller is emphasized. Small signal and transient analysis methods are discussed. This work is directed at developing robust stabilizer design and analysis methods appropriate when fuzzy logic is applied     

Robustness of fuzzy logic power system stabilizers applied tomultimachine power system

This paper investigates the robustness of fuzzy logic power system stabilizers using the information of speed and acceleration states of a study unit. The input signals are the real power output and/or the speed of the study unit. Nonlinear simulations show the robustness of the fuzzy logic power system stabilizers. Experiments are also performed by using a micro-machine system. The results show the feasibility of the proposed fuzzy logic stabilizer     

A fuzzy logic pitch angle controller for power system stabilization

In this article the design of a fuzzy logic pitch angle controller for a fixed speed, active‐stall wind turbine, which is used for power system stabilization, is presented. The system to be controlled, which is the wind turbine and the power system to which the turbine is connected, is described. The advantages of fuzzy logic control when applied to large‐signal control of active‐stall wind turbines are outlined. The general steps of the design process for a fuzzy logic controller, including definition of the controller inputs, set‐up of the fuzzy rules and the method of defuzzification, are described. The performance of the controller is assessed by simulation, where the wind turbine's task is to dampen power system oscillations. In the scenario simulated for this work, the wind turbine has to ride through a transient short‐circuit fault and subsequently contribute to the damping of the grid frequency oscillations that are caused by the transient fault. It is concluded that the fuzzy logic controller enables the wind turbine to dampen power system oscillations. It is also concluded that, owing to the inherent non‐linearities in a wind turbine and the unpredictability of the whole system, the fuzzy logic controller is very suitable for this application. Copyright © 2006 John Wiley &Sons, Ltd.     

Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system

This paper proposes a method of maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic systems. The system is composed of a boost converter and a single-phase inverter connected to a utility grid. The maximum power point tracking control is based on adaptive fuzzy logic to control a switch of a boost converter. Adaptive fuzzy logic controllers provide attractive features such as fast response, good performance. In addition, adaptive fuzzy logic controllers can also change the fuzzy parameter for improving the control system. The single phase inverter uses predictive current control which provides current with sinusoidal waveform. Therefore, the system is able to deliver energy with low harmonics and high power factor. Both conventional fuzzy logic controller and adaptive fuzzy logic controller are simulated and implemented to evaluate performance. Simulation and experimental results are provided for both controllers under the same atmospheric condition. From the simulation and experimental results, the adaptive fuzzy logic controller can deliver more power than the conventional fuzzy logic controller.     

Design of augmented fuzzy logic power system stabilizers to enhancepower systems stability

This paper presents an augmented fuzzy logic power system stabilizer (PSS) for stability enhancement of multimachine power systems. In order to accomplish a satisfactory damping characteristic over a wide range of operating points, speed deviation (Δω) and acceleration (Δω) of a synchronous generator were taken as the input signals to the fuzzy controller. It is well known that these variables have significant effects on damping the generators' shaft mechanical oscillations. A modification of the terminal voltage feedback signal to the excitation system as a function of the accelerating power on the unit, is also used to enhance the stability of the system. The stabilizing signals are computed using the standard fuzzy membership function depending on these variables. The performance of the proposed augmented fuzzy controller is compared to an optimal controller and its effectiveness is demonstrated by a detailed digital computer simulation of a single machine infinite bus and a multimachine power systems     

A fuzzy logic based supervisory controller for an FC/UC hybrid vehicular power system

Depending on growing concerns on energy crises and environmental issues, fuel cell (FC) powered electrical vehicles are favored for possible substitute to conventional internal combustion engine (ICE) based vehicular systems. However, the typical power profile of an automobile motor consisting of transients is not suitable for the use of a sole FC system for vehicle propulsion. This shortcoming could be partly overcome by hybridization. Two potential benefits of combining an FC system with an energy storage unit, ultra-capacitor (UC) has been presented in this study. Firstly, the durability of the FC system could be improved because the additional energy source can fulfill the transient power demand fluctuations. Secondly, the ability of the energy storage source to recover braking energy enhances the fuel economy greatly. An important aspect in designing a hybrid power structure is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. An integrated procedure for mathematical modeling and power control strategy design for an FC/UC hybrid vehicle is presented in this paper. A fuzzy logic supervisory controller based power management strategy that secures the power balance in hybrid structure, enhances the FC performance and minimizes the power losses is proposed. The main contribution of this paper apart from the previous studies of the authors is the modeling of the complete FC power system with air supply compressor and the integration of the control of the FC system internal dynamics (especially the oxygen excess ratio) into the overall supervisory control structure to maximize the efficiency and durability. To demonstrate the effectiveness of the proposed power management scheme, simulation studies were performed using MATLAB^®, Simulink^® and SimPowerSystems^® environments by integrating the detailed mathematical and electrical models of the hybrid vehicular system.     

Lab and field tests of a self-tuning power system stabilizer

Digital power system stabilizers have opened new avenues for applying innovative control strategies to damp generator rotor oscillations at steam and hydroelectric power plants. This paper describes test results from simulation studies and field tests where a self-tuning control algorithm was tested using a digital stabilizer. The simulation studies indicated a marked improvement in local mode damping and a contribution to damping at the inter-area mode while initial tests at power plants gave promising results     

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P&O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P&O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances.     

Theory and method for selection of power system stabilizer location

An approach for the selection of best PSS (power system stabilizer) locations in multimachine power systems is proposed. Study shows that the right-eigenvector measures the activity of state variables and the left-eigenvector measures the control effect of control signals. Based on the right and left eigenvector, the concept of sensitivity of PSS effect (SPE) is presented and used to identify the best PSS locations. The method is used to identify the best PSS location is a 13-machine system to increase the damping of an interarea mode. The time-domain simulation results confirm that the prediction of the best PSS location by the SPE method is correct and accurate     

Adaptive fuzzy logic control of a turbine generator system

This paper is concerned with the application of an adaptive, fuzzy logic controller to a synchronous generator system. Significant reductions in the amount of required calculations have been made which allow a direct analysis of the system. A novel on-line training algorithm is proposed to adapt fuzzy rule base which is shown to converge globally and provide the desired regulation for disturbances at all operating points. The sensitivity of the controller with respect to changes in design parameters is analysed. Test responses are compared with a self-tuning regulator to show the effectiveness of the proposed system. Micromachine tests further establish the possibility of developing a practical controller     

加速功率型电力系统稳定器参数整定方法研究

电力系统稳定器（PSS）是抑制系统低频振荡的有效手段,通常认为以发电机转速偏差和电磁功率偏差为输入信号的加速功率型PSS可避免发电机无功反调问题。结合实例和时域仿真分析,指出在参数整定不合理情况下此类PSS仍可能出现无功反调现象,分析了典型PSS参数对无功反调的影响,在此基础上提出一种基于数字仿真的PSS参数整定方法。对实际电网的时域仿真结果验证了该方法的有效性。     

THD reduction with reactive power compensation for fuzzy logic DVR based solar PV grid connected system

Dynamic voltage restorer (DVR) is used to protect sensitive loads from voltage disturbances of the distribution generation (DG) system. In this paper, a new control approach for the 200 kW solar photovoltaic grid connected system with perturb and observe maximum power point tracking (MPPT) technique is implemented. Power quality improvement with comparison is conducted during fault with proportional integral (PI) and artificial intelligence-based fuzzy logic controlled DVR. MPPT tracks the actual variable DC link voltage while deriving the maximum power from a photovoltaic array and maintains DC link voltage constant by changing modulation index of the converter. Simulation results during fault show that the fuzzy logic based DVR scheme demonstrates simultaneous exchange of active and reactive power with less total harmonic distortion (THD) present in voltage source converter (VSC) current and grid current with fast tracking of optimum operating point at unity power factor. Standards (IEEE-519/1547), stipulates that the current with THD greater than 5% cannot be injected into the grid by any distributed generation source. Simulation results and validations of MPPT technique and operation of fuzzy logic controlled DVR demonstrate the effectiveness of the proposed control schemes.     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS     

An interval type-2 fuzzy logic controller for TCSC to improve the damping of power system oscillations

In this paper an interval type-2 fuzzy logic controller (IT2FLC) was proposed for thyristor controlled series capacitor (TCSC) to improve power system damping. For controller design, memberships of system variables were represented using interval type-2 fuzzy sets. The three-dimensional membership function of type-2 fuzzy sets provided additional degree of freedom that made it possible to directly model and handle uncertainties. Simulations conducted on a single machine infinite bus (SMIB) power system showed that the proposed controller was more effective than particle swarm optimization (PSO) tuned and type-1 fuzzy logic (T1FL) based damping controllers. Robust performance of the proposed controller was also validated at different operating conditions, various disturbances and parameter variation of the transmission line parameters.