一种基于规则和学习算法设计的电力系统智能PID控制器

提出了一种基于规则和学习算法设计的电力系统智能ＰＩＤ控制器的设计方法。通过对固定参数电力系统ＰＩＤ控制器性能的研究，验证并获得了一些关于电力系统电压和稳定性控制协调与鲁棒性的结论。在此基础上，研制出一种智能ＰＩＤ控制器，它由基于规则的开关控制和基于学习控制的算法组成。在单机无穷大电力系统中应用的非线性仿真表明，这种智能ＰＩＤ控制器满足电力系统电压和稳定性协调控制的要求，且具有较强的鲁棒性。     

Smart control techniques for design of TCSC and PSS for stability enhancement of dynamical power system

This paper deals with the simultaneous application of thyristor controlled series capacitor based damping controller and power system stabilizer for stability improvement of dynamic power system. The adaptive neuro-fuzzy inference system and Levenberg–Marquardt artificial neural network algorithm are used to develop the control strategy for thyristor controlled series capacitor based damping controller and power system stabilizer. The power system stabilizer generates appropriate supplementary control signal to an excitation system of synchronous generator to damp the frequency oscillations and improves the performance of the power system dynamic. The performance of power system affected due to the system configuration and load variation. In order to achieve the appreciable damping, the series capacitor is suggested in addition to the power system stabilizer. Nonlinear simulations of single machine infinite bus system are carried out using the individual application of power system stabilizer and simultaneous application of power system stabilizer and thyristor controlled series capacitor. The comparison analysis between conventional and smart control strategies based controllers is demonstrated. Single machine infinite bus system is tested under various operating conditions and disturbances to show the effectiveness of proposed control schemes.     

Nonlinear control design for excitation controller and power system stabilizer

The paper focuses on the design of excitation controller and power system stabilizer (PSS) control schemes to enhance voltage regulation and transient stability. To design the excitation controller, the nonlinear models of the synchronous generator and electrical system are suitably arranged to give an input-output nonlinear model, which is subsequently made linear by a compensating law. The PSS control scheme is designed according to a new approach, based on the inverse system theory, which guarantees satisfactory swing damping by reducing the mutual influence between transient stability and voltage regulation. The results obtained by numerical simulations in different operating conditions confirm the effectiveness of the proposed design, also in the presence of model parameter inaccuracy.     

Decentralized multivariable voltage and speed regulator for large-scale power systems with guarantee of stability and transient performance

This paper presents a novel procedure for the design of decentralized regulators for large power systems with a formal proof of ‘global’ stability. The distinctive feature of the solution is that both voltage and rotor speed dynamics are regulated simultaneously contrary to most of the solutions proposed so far in the literature. First, the traditional multimachine power system algebraic-differential equations are reformatted into suitable state equations, more appropriate for modern control tools. Secondly, a voltage and speed controller based on this model is proposed. The design consists of first cancelling some of the dynamical model non-linearities using non-linear excitation and valve input. The resulting subsystems are stabilized by auxiliary controls with linear and non-linear components. The non-linear component, which uses local signals to dominate those with interconnections, is derived from a stability criterion involving the Lyapunov function of the entire power system. The gains of the linear component are computed from the solution of an algebraic Riccati equation similar to the one involved in the full information H _∞ problem. These gains guarantee that effects of interconnection signals on voltage and speed dynamics are considerably reduced. The benefit of the proposed scheme is that the voltage regulation characteristic ensures a good post-fault voltage profile which helps improve rotor oscillations damping. Simulation results on a realistic power system confirm that the system stability is considerably improved in presence of severe contingencies.     

Decentralized Nonlinear Robust Coordinated Control of UPFC and Generators in Multi‐ Machine Power System Via Pseudo‐Generalized Hamiltonian Theory

In this paper, based on a structure preserving power system with a unified power flow controller (UPFC), using pseudo‐generalized Hamiltonian function method and boundary‐function method, a nonlinear robust coordinated control law is constructed for multi‐machine power system oscillation damping. The 4‐machine 2‐area power system is used to demonstrate the performance of the proposed controller. Simulation results indicate that the proposed coordinated control scheme can effectively improve both transient stability and voltage regulation performance of the power system. ©2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd     

基于模糊和PI控制的MIG焊接电源设计

针对模拟控制和单片机控制的脉冲MIG(Metal Inert Gas)弧焊电源控制系统灵活性差、控制精度低和可靠性差等缺点,设计了基于模糊和PI控制的MIG焊接电源控制系统。为了提高焊接电流的控制精度,控制焊接电流的PI参数在一个周期的不同阶段应该是不同,所以该系统的焊接电流控制采用变参数PI控制方法。在不同焊接条件下的PI参数由专家系统确定。为了提高电弧弧长的稳定性,电弧电压控制采用模糊控制方法。模糊控制和变参数PI控制算法分别由数字信号控制器(DSC)和现场可编程门阵列(FPGA)实现。最后,介绍了系统的硬件电路设计和软件流程。利用焊接铝板对该系统进行了测试,测试结果表明,基于模糊和PI控制的MIG焊接电源控制系统动态响应快、可靠性高、弧长控制稳定。     

Improved Design of Interval Type-2 Fuzzy based Wide Area Power System Stabilizer for Inter-area Oscillation Damping

The interconnection of power system due to the ever-time increase in power demand has caused inter-area oscillations as a challenge to power system stability. The present paper proposes the novel design of an Interval Type-2 Fuzzy based Wide Area Power System Stabilizer to damp the inter-area mode of oscillations for improving the power system stability. The usage of Wide Area Measurement Systems for continuous monitoring of the power grid plays a significant role in maintaining the stability of the power grid. The proposed controller uses wide-area signals from WAMS as the input signals. The controllability index calculation performs the selection of the most affected wide-area signals. The participation factor is used to identify the location of the controller. Sliding Surface approach is introduced in the controller to upgrade the performance of the controller during different operating conditions. The sliding surface approach has made the system insensitive to the parameter variations. The interval type-2 fuzzy control is a model-free approach with better control performance, due to its higher degree of freedom of interval type-2 fuzzy sets. Finally, the optimal tuning of sliding surface parameters has been considered as an optimization problem with the minimization of Integral Time Square Error using Real Coded Genetic Algorithm to enhance the damping control. The proposed Fuzzy controller has been tested in two area, four machine, 11 bus IEEE benchmark system. From the simulation responses and the comparison with different controllers, the proposed controller shows robustness and effectiveness with more accurate dynamic response and better damping of inter-area oscillations under different system operating conditions and load perturbations.     

An advanced FMRL controller for FACTS devices to enhance dynamic performance of power systems

The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system (FACTS) in this paper is an advanced super-conducting magnetic energy storage (ASMES). Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller (FMRLC) is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters (i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met). Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system (i.e., single machine-infinite bus (SMIB) system), under various fault conditions and disturbances.     

Approximated fuzzy logic controlled shunt active power filter for improved power quality

Shunt active power filters have been widely used for power quality improvement. With the advancement in artificial intelligence techniques, the applications of fuzzy logic‐based control systems have increased manifolds. This paper proposes a reduced rule fuzzy logic controller (FLC) in the voltage control loop of a shunt active power filter (APF), which is approximating a conventional large rule FLC. The difference between the controlled outputs of two controllers is compensated by proposed compensating factors. The dynamic response and harmonic compensation performance of proposed 4‐rule approximated fuzzy logic controller (AFLC) is compared with 25‐rule FLC. A three‐phase shunt APF is used for harmonic and reactive power compensation. The proposed scheme is tested with randomly varying single and multiple non‐linear loads. The simulation results presented under transient and steady‐state conditions confirm that the proposed 4‐rule AFLC efficiently approximates the 25‐rule FLC. The proposed control methodology takes less computational time and computational memory as the numbers of rules are reduced significantly.     

Cuckoo search (CS)-NFC-based UPQC for compensating voltage sag of nonlinear load

In this paper, a cuckoo search (CS) algorithm-based neuro-fuzzy controller (NFC) is developed to improve the performance of unified power quality conditioner (UPQC). The CS algorithm is used for optimising the output of neural network (NN) so that the classification output of the NN is enhanced. The inputs of the networks are error and change of error voltage of the PQ issue signal of nonlinear load which are calculated by comparison with the reference signal. Next, the output of network, i.e. regulated (compensated) voltage, is optimised by the CS algorithm. From the output of CS, an optimum rule-based fuzzy interference system is developed and the PQ problem is compensated. The CS-NFC-based UPQC is implemented in MATLAB/Simulink and the PQ issue clearing performance is analysed. The PQ issue clearing performance of proposed UPQC is compared with traditional UPQC, NFC-UPQC, GA-NFC-UPQC and adaptive GA-NFC-UPQC. The CS-NFC-based UPQC controller has lesser error deviation of 2.8% with traditional UPQC, 2.12% with NFC, 1.7% with GA-NFC and 0.6% with adaptive GA-NFC.     

A type-2 fuzzy logic controller design for buck and boost DC–DC converters

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cause rule uncertainty problems. Consequently, the performance of the controlled system, which is controlled with type-1 fuzzy logic controller, is undesirably affected. In this study, a type-2 fuzzy logic controller is proposed for the control of buck and boost DC–DC converters. To examine and analysis the effects of the proposed controller on the system performance, both converters are also controlled using the PI controller and conventional fuzzy logic controller. The settling time, the overshoot, the steady state error and the transient response of the converters under the load and input voltage changes are used as the performance criteria for the evaluation of the controller performance. Simulation results show that buck and boost converters controlled by type-2 fuzzy logic controller have better performance than the buck and boost converters controlled by type-1 fuzzy logic controller and PI controller.     

A robust integrator algorithm with genetic based fuzzy controller feedback for direct vector control

The voltage model used for direct vector control has in the flux calculation process an open integration problem, which is generally solved with a feedback loop. In this paper, a new design method is developed for the feedback loop of the integrator. The method, as apart from standards in the literature, uses a fuzzy controller. Fuzzy controllers are knowledge-based systems that include fuzzy rules and fuzzy membership functions to incorporate human knowledge into their knowledge base. The determination of these rules and membership functions is one the key problems when designing fuzzy controllers, and is generally affected by subjective decisions. In this study, a fuzzy controller with rules and membership functions determined by genetic algorithms (GAs) in this study is designed and tested on various motors of different power ratings. The proposed method is simulated by using MATLAB/SIMULINK and implemented on an experimental system using a TMS320C31 digital signal processor.     

Hybrid Adaptive Type‐2 Fuzzy Tracking Control of Chaotic Oscillation Damping of Power Systems

In this paper a novel hybrid direct/indirect adaptive fuzzy neural network (FNN) moving sliding mode tracking controller for chaotic oscillation damping of power systems is developed. The proposed approach is established by providing a tradeoff between the indirect and direct FNN controllers. It is equipped with a novel moving sliding surface (MSS) to enhance the robustness of the controller against the present system uncertainties and unknown disturbances. The major contribution of the paper arises from the new simple tuning idea of the sliding surface slope and intercept of the MSS. This study is novel because the approach adopted tunes the sliding surface slope and intercept of MSS using two simple rules simultaneously. One advantage of the proposed approach is that the restriction of knowing the bounds of uncertainties is also removed due to the adaptive mechanism. Moreover, the stability of the control system is also presented. The proposed controller structure is successfully employed to damp the complicated chaotic oscillations of an interconnected power system, when such oscillations can be made by load perturbation of a power system working on its stability edges. Comparative simulation results are presented, which confirm that the proposed hybrid adaptive type‐2 fuzzy tracking controller shows superior tracking performance.     

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.     

用于抑制电压闪变的DSTATCOM模糊自适应整定PI控制

DSTATCOM采用直接电流控制方法来抑制由于波动性负荷引起的电压闪变时,其无功电流的跟踪性能对装置的抑制效果起着决定性的作用.考虑到常规PI控制在设计控制器时参数整定的困难和电网参数动态变动的特性,提出利用模糊逻辑对PI控制器的参数进行在线调整,使得DSTATCOM具有很强的自适应性和鲁棒性.当电网参数发生变化时,DSTATCOM仍能很好的抑制电压闪变.数字仿真结果验证了控制策略的正确性和有效性.     

Most Suitable Power System Stabilizer Selection for the Improvement of Dynamic Stability

A method of enhancing power system stability for a single machine to infinite bus power system is presented. The technique used compromises the effectiveness of Proportional-Integral-Derivative controller (PID). In order to satisfy the damping characteristics for the proposed power system over a wide range of operating interval, rotational speed, torque angle and terminal voltage signals of the synchronous machine are utilized as control signals of the system. It is well known that these variables have sign...     

An Adaptive Passivity‐Based Controller of a Buck‐Boost Converter with a Constant Power Load

This paper addresses the problem of regulating the output voltage of a DC‐DC buck‐boost converter feeding a constant power load, which is a problem of current practical interest. Designing a stabilising controller is theoretically challenging because its average model is a bilinear second order system that, due to the presence of the constant power load, is non‐minimum phase with respect to both states. Moreover, to design a high‐performance controller, the knowledge of the extracted load power, which is difficult to measure in industrial applications, is required. In this paper, an adaptive interconnection and damping assignment passivity‐based control—that incorporates the immersion and invariance parameter estimator for the load power—is proposed to solve the problem. Some detailed simulations are provided to validate the transient behaviour of the proposed controller and compare it with the performance of a classical PD scheme.     

模糊PID控制策略在动态电压恢复器中的应用研究

针对动态电压恢复器采用前馈控制方法和PID控制方法处理电压跌落问题的不足,提出了一种模糊PID控制策略。该控制策略实现原理:当电网电压检测系统检测到供电端电压发生跌落时,使动态电压恢复器投入到电网中运行;由标准信号产生模块产生与电网电压同步的标准正弦信号,用该信号与实际电网电压进行比较;然后通过模糊PID控制器调节得到需要实际补偿的电压给定信号,并利用控制环节生成逆变器所需要的PWM信号,通过驱动电路去控制逆变器功率开关的通断;逆变器输出电压经滤波后通过串联变压器注入电网,产生补偿电压用于抵消电网电压的波动。仿真结果验证了该控制策略的有效性。     

Application of Fuzzy Logic Controlled Cathodic Protection on Iraq-Turkey Crude Oil Pipeline

Impressed current cathodic protection is widely used to prevent corrosion of structural steels. The major constituents, which accelerate corrosion, are resistivity, chlorides, sulfatesand the acidity (pH) of the soil. Because of these variations, the transformer-rectifier units must control and tune the output voltage depending on desired reference voltage steadily. Usually, classical controls such as PI and PID, have been widely used with their gains manually tuned based on the desired reference voltage. But, classical controls require different gains at the lower and higher end of the output voltage range to avoid overshoot and oscillation. In this study, a closed loop control system incorporating fuzzy logic has been developed for tuning output voltage of the transformer-rectifier units. The algorithm based on fuzzy logic was implemented on a modern microcontroller (PIC16F877) allowing great flexibility for various real time applications. The desired reference voltage has been given by using keypad and output values have been displayed on an LCD. It is achieved by implementing an adaptation mechanism based on fuzzy logic controller to compensate for the variations and the dynamic changes in the environment. The proposed fuzzy logic controller was applied to two different areas on Iraq-Turkey crude oil pipeline. When the performance of the proposed fuzzy logic controller was observed, it has been seen that the output voltage of transformer-rectifier unit controlled by fuzzy logic controller has no overshoot and oscillation in the both areas.