A fuzzy logic excitation system for stability enhancement of powersystems with multi-mode oscillations

A fuzzy logic excitation system has been proposed to enhance the overall stability of power systems. The proposed excitation system has two control loops. One is the voltage control loop which achieves the automatic voltage regulator (AVR) function, and the other is the damping control loop which gives the PSS function. Simple fuzzy logic control rules are applied to both loops. The input signal to the voltage control loop is the terminal voltage, and the input signal to the damping control loop is the real power output. Simulation studies show the advantages of the fuzzy logic excitation system     

Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive

In this paper a fuzzy logic (FL) based model reference adaptive system (MRAS) speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller (FLC) for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic (PV) energy source is used. To extract the maximum power from the PV source, a constant voltage controller (CVC) is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.     

Doubly-fed induction generator drive based WECS using fuzzy logic controller

The purpose of this paper is to improve the control performance of the variable speed, constant frequency doubly-fed induction generator in the wind turbine generation system by using fuzzy logic controllers. The control of the rotor-side converter is realized by stator flux oriented control, whereas the control of the grid-side converter is performed by a control strategy based on grid voltage orientation to maintain the DC-link voltage stability. An intelligent fuzzy inference system is proposed as an alternative of the conventional proportional and integral (PI) controller to overcome any disturbance, such as fast wind speed variation, short grid voltage fault, parameter variations and so on. Five fuzzy logic controllers are used in the rotor side converter (RSC) for maximum power point tracking (MPPT) algorithm, active and reactive power control loops, and another two fuzzy logic controllers for direct and quadratic rotor currents components control loops. The performances have been tested on 1.5 MW doubly-fed induction generator (DFIG) in a Matlab/Simulink software environment.     

Fuzzy logic controller implementation for a solar air-conditioning system

The implementation of a variable structure fuzzy logic controller for a solar powered air conditioning system and its advantages are investigated in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. Two different control schemes for the DC motors rotational speed adjustment are implemented and tested: the first one is a pure fuzzy controller, its output being the control signal for the DC motor driver. A 7 × 7 fuzzy matrix assigns the controller output with respect to the error value and the derivative of the error. The second scheme is a two-level controller. The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller. Step response of the two control loops are presented as experimental results. The contribution of this design is that in the control system, the fuzzy logic is implemented through software in a common, inexpensive, 16-bit microcontroller, which does not have special abilities for fuzzy control.     

A new control strategy for a stand-alone self-excited induction generator driven by a variable speed wind turbine

This paper presents a new control strategy of a stand-alone self-excited induction generator (SEIG) driven by a variable speed wind turbine. The proposed system consists of a three phase squirrel-cage induction machine connected to a wind turbine through a step-up gear box. A current controlled voltage source inverter (CC–VSI) with an electronic load controller (ELC) is connected in parallel with the main consumer load to the AC terminals of the induction machine. The proposed control strategy is based on fuzzy logic control principles which enhance the dynamic performance of the proposed system. Three fuzzy logic PI controllers and one hysteresis current controller (HCC) are used to extract the maximum available energy from the wind turbine as well as to regulate the generator terminal voltage simultaneously against wind speed and main load variations. However, in order to extract the maximum available energy from the turbine over a wide range of wind speeds, the captured energy is limited due to electrical constraints. Therefore the control strategy proposed three modes of control operation. The steady state characteristics of the proposed system are obtained and examined in order to design the required control parameters. The proposed system is modeled and simulated using Matlab/Simulink software program to examine the dynamic characteristics of the system with proposed control strategy. Dynamic simulation results demonstrate the effectiveness of the proposed control strategy.     

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     

Hybrid fuzzy controller for speed control of switched reluctance motor drives

A hybrid fuzzy controller for speed control of switched reluctance motor (SRM) drives is presented in this paper. The developed hybrid fuzzy control law consists of a proportional integral (PI) controller at steady state, a PI type fuzzy logic controller (FLC) at transient state and a simple logic controller between the steady and transient states to achieve the desired performance at various operating conditions under soft chopping operation. The importance of the hybrid fuzzy controller is highlighted by comparing the performance of various control approaches, including PI control, PI type fuzzy logic control and PD type fuzzy control for speed control of SRM motor drives. The complete control algorithm is demonstrated by intensive experimental results. It is shown that the presented hybrid controller for SRM drive has fast tracking capability, less steady state error and is robust to load disturbance. The complete speed control scheme of the SRM drive incorporating the hybrid control is experimentally implemented and validated using a high speed digital signal processor board TMS320F2812 for a prototype 1.2 kW SRM.     

Power quality improvement using fuzzy logic controller for five-level shunt active power filter under distorted voltage conditions

In this paper, a five-level inverter is used as a shunt active power filter (APF), taking advantages of the multilevel inverter such as low harmonic distortion and reduced switching losses. It is used to compensate reactive power and eliminate harmonics drawn from a thyristor rectifier feeding an inductive load (RL) under distorted voltage conditions. The APF control strategy is based on the use of self-tuning filters (STF) for reference current generation and a fuzzy logic current controller. The use of STF instead of classical extraction filters allows extracting directly the voltage and current fundamental components in the α-β axis without phase locked loop (PLL). The MATLAB fuzzy logic toolbox is used for implementing the fuzzy logic control algorithm. The obtained results show that the proposed shunt APF controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the line voltage.     

Fuzzy logic application for intelligent control of a variable speeddrive

The slip power recovery configuration is an attractive scheme of variable speed drive, with high efficiency and low power converter rating; however, high performance control has been difficult. In this paper, novel applications of fuzzy logic for the intelligent control of a slip power recovery system are presented. A direct fuzzy logic controller and an adaptive fuzzy controller, based on model reference adaptive control, are developed and simulated for the doubly-excited induction machine and power converter system. Compared with field orientation control, the intelligent control of a complex slip power recovery system reduces costs and enhances robust and desired performance     

Enhancement of micro-grid performance during islanding mode using storage batteries and new fuzzy logic pitch angle controller

Power system deregulation, shortage of transmission capacities and needing to reduce green house gas have led to increase interesting in distributed generations (DGs) especially renewable sources. This study developed a complete model able to analysis and simulates in details the transient dynamic performance of the Micro-Grid (MG) during and subsequent islanding process. Wind speed fluctuations cause high fluctuations in output power of wind turbine which lead to fluctuations of frequency and voltages of the MG during the islanding mode. In this paper a new fuzzy logic pitch angle controller is proposed to smooth the output power of wind turbine to reduce MG frequency and voltage fluctuations during the islanding mode. The proposed fuzzy logic pitch controller is compared with the conventional PI pitch angle controller which usually used for wind turbine power control. Results proved the effectiveness of the proposed fuzzy controller in improvement of the MG performance. Also, this paper proposed using storage batteries technique to reduce the frequency deviation and fluctuations originated from wind power solar power fluctuations. Results indicate that the storage batteries technique is superior than fuzzy logic pitch controller in reducing frequency deviation, but with more expensive than the fuzzy controller. All models and controllers are built using Matlab® Simulink® environment.     

Neuro-fuzzy control for autonomous wind–diesel systems using biomass

This paper deals with the development of a neuro-fuzzy controller for a wind–diesel system composed of a stall regulated wind turbine with an induction generator connected to an ac bus-bar in parallel with a diesel generator set having a synchronous generator. A gasifier is capable of converting tons of wood chips per day into a gaseous fuel that is fed into a diesel engine. The controller inputs are the engine speed error and its derivative for the governor part of the controller, and the voltage error and its derivative for the automatic voltage regulator. These are readily measurable quantities leading to a simple controller which can be easily implemented. It is shown that by tuning the fuzzy logic controllers, optimal time domain performance of the autonomous wind–diesel system can be achieved in a wide range of operating conditions compared to fixed-parameter fuzzy logic controllers and PID controllers.     

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     

Voltage and frequency control of self-excited slip-ring induction generators

By varying the effective rotor resistance of a self-excited slip-ring induction generator (SESRIG), the magnitude and frequency of the output voltage can be controlled over a wide speed range. A steady-state analysis based on a normalized equivalent circuit enables the control characteristics to be deduced. For a given stator load impedance, both the frequency and the voltage can be maintained constant as the speed is varied, without changing the excitation capacitance. When the stator load is variable, simultaneous voltage and frequency control requires the excitation capacitance to be changed as the rotor resistance is varied. Experiments performed on a 1.8-kW laboratory machine confirm the feasibility of the method of control. Practical implementation of a closed-loop control scheme for an SESRIG using chopper-controlled rotor resistance is also discussed. With a properly tuned proportional-plus-integral (PI) controller, satisfactory dynamic performance of the SESRIG is obtained. The proposed scheme may be used in a low-cost variable-speed wind energy system for providing good-quality electric power to remote regions.     

基于模糊推理的摩托车速度特性测试系统

本文介绍了基于电涡流测功机的摩托车发动机速度特性测试系统，给出了转速控制系统的结构，提出了基于模糊逻辑控制器的转速控制器及采用Mamdani算法实现模糊逻辑控制器的推理。着重介绍了实现Mamdani算法的C语言程序。该程序具有简捷、易于实现和移植好等特点。实验表明该速度特性测试系统是合理的，并能获得满意的控制效果。     

Design and real time implementation of type-2 fuzzy vector control for DFIG based wind generators

Doubly fed induction generator is very sensitive to voltage variations in the grid, which pose limitation for wind power plants during the grid integrated operation. Handling the uncertainity in wind speed and grid faults is a major challenge to fulfill the modern grid code requirements. This paper proposes a new control strategy for Rotor side converter using Interval type-2 fuzzy sets which can model and handle uncertainties in the system parameters. The presence of third dimension in the membership function, offers an additional degree of freedom in the design of the controller to counter the effects of fluctuations in wind speed and low voltage during severe grid fault conditions. A 2 MW DFIG connected to the grid is modelled in simulation software RSCAD and interfaced with Real time digital simulator (RTDS) to perform the simulations in real-time. The RTDS platform is considered by many research laboratories as real-time testing module for controller prototyping and also for hardware in the loop (HIL) applications. The controller performance is evaluated in HIL configuration, by performing the real-time simulations under various parameter uncertainties. The proposed controller can improve the low voltage ride through capability of DFIG compared to that of PI and type-1 fuzzy controller.     

Adaptive fuzzy control for wind-diesel weak power systems

This work is concerned with the development of an adaptive fuzzy logic controller for a wind-diesel system composed of a stall regulated wind turbine with an induction generator connected to an AC busbar in parallel with a diesel generator set having a synchronous generator. In this work we propose to use an adaptive network based inference system (ANFIS) in order to generate fuzzy membership functions and control rules for the controller. A feedback linearized proportional integral controller is used to provide the required expert knowledge. A controller design process is identified; it consists of generating input-output data pairs to identify the control variables range and initial fuzzy memberships, and then to tune or adapt them using an ANFIS network structure. The controller inputs are the frequency error and its integral for the governor part of the controller, and the voltage and frequency errors for the automatic voltage regulator. These are readily measurable quantities leading to a simple controller which can be easily implemented     

Fuzzy logic control based maximum power tracking of a wind energy system

In this paper a utility interactive wind energy conversion system (WECS) with an asynchronous (AC–DC–AC) link is described. The control system has the objective of identifying and extracting the maximum power from the wind energy system and transferring this power to utility. A fuzzy logic control (FLC) technique has been implemented to design the tracking controller of the WECS. A wind speed step model was used in the design phase. The performance of the WECS with the proposed fuzzy logic controller is tested using real meteorological data. Its robustness and effectiveness are demonstrated by the simulation results of the controlled system.     

Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions

The one of main causes of reducing energy yield of photovoltaic systems is partially shaded conditions. Although the conventional maximum power point tracking (MPPT) control algorithms operate well under uniform insolation, they do not operate well in non-uniform insolation. The non-uniform conditions cause multiple local maximum power points on the power?voltage curve. The conventional MPPT methods cannot distinguish between the global and local peaks. Since the global maximum power point (MPP) may change within a large voltage window and also its position depends on shading patterns, it is very difficult to recognise the global operating point under partially shaded conditions. In this paper, a novel MPPT system is proposed for partially shaded PV array using artificial neural network (ANN) and fuzzy logic with polar information controller. The ANN with three layer feed-forward is trained once for several partially shaded conditions to determine the global MPP voltage. The fuzzy logic with polar information controller uses the global MPP voltage as a reference voltage to generate the required control signal for the power converter. Another objective of this study is to determine the estimated maximum power and energy generation of PV system through the same ANN structure. The effectiveness of the proposed method is demonstrated under the experimental real-time simulation technique based dSPACE real-time interface system for different interconnected PV arrays such as series-parallel, bridge link and total cross tied configurations.     

基于模糊PI控制的海上风电柔性直流输电整流器研究

为提高海上风电柔性直流输电电压等级,抑制直流侧电压跌落和闪变,将三相电压源变流器用于送端整流器。采用多个功率单元级联的拓扑结构,电流内环采用PI解耦控制、电压外环模糊PI调节双闭环控制方式。分析了变流器数学模型,建立了MATLAB／Simulink仿真模型,实现了电压级联输出．在线PI参数整定。仿真结果验证了该系统在海上风电柔性直流输电应用中的有效性。     

Grid Synchronization of Doubly-fed Induction Generator Using Integral Variable Structure Control

This paper proposes a novel direct voltage control scheme, using integral variable structure control to synchronize a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) to the grid. The proposed scheme directly controls the stator terminal voltage of the DFIG to track the grid voltage without current control loop; hence, the structure of controller is simplified. The control scheme includes parametric uncertainty and external disturbances into the formed design procedure; hence, the proposed scheme has better robustness than existing synchronization methods. Both computer simulation and hardware implementation results are presented to demonstrate the advantages of the proposed scheme.