A fuzzy logic controlled superconducting magnetic energy storage,SMES frequency stabilizer

This paper presents application of fuzzy logic controlled superconducting magnetic energy storage device, SMES to damp the frequency oscillations of interconnected two-area power systems due to load excursions. The system frequency oscillations appear due to load disturbance. To stabilize the system frequency oscillations, the active power can be controlled via superconducting magnetic energy storage device, SMES. The error in the area control and its rate of change is used as controller input signals to the proposed fuzzy logic controller. In order to judge the effect of the proposed fuzzy logic controlled SMES, a comparative study is made between its effect and the effect of the conventional proportional plus integral (PI) controlled SMES. The studied system consists of two-area (thermal–thermal) power system each one equipped with SMES unit. The time simulation results indicate the superiority of the proposed fuzzy logic controlled SMES over the conventional PI SMES in damping the system oscillations and reach quickly to zero frequency deviation. The system is modeled and solved by using MATLAB software.     

Minimization of shaft oscillations by fuzzy controlled SMES considering time delay

This paper analyzes the effect of fuzzy logic-controlled superconductive magnetic energy storage (SMES) on minimizing shaft torsional oscillations of synchronous generators in a multi-machine power system. The proposed fuzzy logic controller has been designed in a very simple way considering only one input variable and one output variable. The time derivative of the total kinetic energy deviation (TKED) of the synchronous generators is used as the global input to the fuzzy controller for SMES switching. The influence of time delay associated with the global input calculation of the fuzzy controller on minimizing shaft torsional oscillations is investigated. Global positioning system (GPS) is proposed for the practical implementation of the calculation of the global input to the fuzzy controller. Simulation results of a balanced fault at different points in a multi-machine power system show that the proposed SMES can minimize the shaft torsional oscillations of synchronous generators well. Moreover, the time delay has an influence on the performance of fuzzy controlled SMES to minimize shaft torsional oscillations. However, even though the performance of fuzzy controlled SMES is somewhat effected by the communication delay, it is clear from the simulation responses that the fuzzy logic-controlled SMES considering typical communication delays can minimize the shaft torsional oscillations of synchronous generators well.     

超导磁储能系统抑制风力发电功率波动的研究

建立含超导磁储能装置(SMES)的单机无穷大系统的Phillips-Heffron模型,导出含SMES电力系统总的电磁转矩表达式,从理论上分析SMES对增强系统阻尼的作用.并设计了SMES非线性比例积分微分控制器,数字仿真结果验证了SMES阻尼系统功率振荡的特性,同时表明该控制器具有较好的鲁棒性.     

A control strategy for leveling load power fluctuations with a successive learning fuzzy-neural network based on prediction of average load power

The effective usage of power facilities can be realized by leveling the fluctuating active power and compensating the reactive power. A fuzzy control strategy of superconducting magnetic energy storage (SMES) has been proposed for this purpose. The control results depend on the values of the scaling factors in fuzzy reasoning. Therefore, to obtain better control results, the scaling factor should be successively adjusted according to the load power fluctuations. In this paper, a control strategy based on autotuning of scaling factors and a fuzzy singleton reasoning method using backpropagation in a neural network is proposed for leveling load fluctuations. The prediction and revision of the teaching signal in terms of the energy of the SMES is proposed. The learning rate and the revision of the teaching signal are discussed. Better leveling of load power fluctuation is shown to be achievable by using fuzzy logic and neural networks. © 1997 Scripta Technica, Inc. Electr Eng Jpn, 120(2): 72–81, 1997     

Power-system stabilizing control by SMES using fuzzy techniques and neural networks

It has been clarified that a superconducting magnetic energy storage (SMES) is very effective for power system stabilization. The control methods proposed for power system stabilization by SMES include the pole assignment, the optimum control, and so on, each of which, however, has its drawbacks. The application of fuzzy control is considered to overcome these drawbacks. This paper considers the power system stabilization by fuzzy control of the active and reactive power of SMES. First, the adequate fuzzy control rules of an SMES for the model power system is derived. Then, to alleviate the dependence of the fuzzy control on the operating condition and the fault, a method is proposed which adjusts the fuzzy parameter according to the operating condition and the fault using a neural network. The validity of the proposed method is examined by computer simulations.     

Enhancement of transient stability by fuzzy logic-controlled SMES considering communication delay

This paper presents a fuzzy logic-controlled superconducting magnetic energy storage (SMES) for the enhancement of transient stability in a multi-machine power system. The control scheme of SMES is based on a pulse width modulation (PWM) voltage source converter (VSC) and a two-quadrant DC–DC chopper using gate-turn-off (GTO) thyristor. Total kinetic energy deviation (TKED) of the synchronous generators is used as the fuzzy input for SMES control. Communication delays introduced in online calculation of the TKED are considered for the actual analysis of transient stability. Global positioning system (GPS) is proposed for the practical implementation of the calculation of the TKED. Simulation results of balanced fault at different points in a multi-machine power system show that the proposed fuzzy logic-controlled SMES is an effective device for transient stability enhancement of multi-machine power system. Moreover, the transient stability performance is effected by the communication delay.     

A fuzzy logic‐controlled SMES for damping shaft torsional oscillations of synchronous generator

This paper presents a fuzzy logic control scheme for the superconducting magnetic energy storage (SMES) based on a PWM voltage source converter and a two‐quadrant chopper using an insulated‐gate‐bipolar‐transistor (IGBT) to dampen turbine‐generator shaft torsional oscillations. Simulation results of balanced faults in a single machine connected to an infinite bus system show that the proposed fuzzy logic‐controlled SMES is effective in damping shaft torsional oscillations of synchronous generators (GENs). © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Application of simultaneous active and reactive power modulation ofSMES unit under unequal α-mode for power system stabilization

A simple and novel control strategy for damping electromechanical oscillations through control of power converter firing angles α ₁ and α₂ of a superconducting magnetic energy storage (SMES) unit is proposed. Both active and reactive power modulations are used under unequal α-mode of operation. The choice of unequal mode is discussed in detail. The gains of the proposed SMES controller are determined once offline depending on the power system and the rating of the SMES unit. Simulation results show that the SMES unit can effectively suppress power system oscillations by utilizing its active and reactive power modulation capabilities. The control algorithm is simple and its realization will require very little hardware     

A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system

The intermittent wind power in isolated hybrid distributed generation (IHDG) may cause serious problems associated with frequency (f) and power (P) fluctuation. Energy storage devices such as battery, super capacitor, and superconducting magnetic energy storage (SMES) may be used to reduce these fluctuations associated with f and P. This paper presents a study of IHDG power system for improving both f and P deviation profiles with the help of SMES. The studied IHDG power system is consisted of wind turbine generator and diesel engine generator. Both f and P control problems of the studied power system model are addressed in presence or absence of SMES. Fuzzy logic based proportional–integral–derivative (PID) controller with SMES is used for the purpose of minimization of f and P deviations. The different tunable parameters of the PID controller and those of the SMES are tuned by a novel quasi-oppositional harmony search algorithm. Performance study of the IHDG power system model is carried out under different perturbation conditions. The results demonstrate minimum f and P deviations may be achieved by using the proposed fuzzy logic based PID controller along with SMES.     

超导储能改善并网风电场稳定性的研究

建立了风电机组和超导储能(SMES)装置的数学模型以研究SMES对并网风电场运行稳定性的改善.针对风电系统中经常出现的联络线短路故障和风电场的风速扰动,提出利用SMES安装点的电压偏差作为SMES有功控制器的控制信号的策略.对实例系统进行的仿真计算结果表明,SMES采用该控制策略,不仅可以在网络故障后有效地提高风电场的稳定性,而且能够在快速的风速扰动下平滑风电场的功率输出,降低风电场对电网的冲击.     

超导储能装置应用于风电场平滑功率输出的研究

建立了风电机组和超导储能(superconducting magnetic energy storage,SMES)装置的数学模型以研究SMES对并网风电场运行稳定性的改善。针对风电系统中经常出现的联络线短路故障和风电场的风速扰动,提出利用SMES安装点的电压偏差作为SMES有功控制器的控制信号的策略。并搭建了风电场接入电网后的仿真模型,对实例系统进行的仿真计算结果表明,SMES采用该控制策略,不仅可以在网络故障后有效地提高风电场的稳定性,而且能够在快速的风速扰动下平滑风电场的功率输出,降低风电场对电网的冲击。     

Augmentation of transient stability using a superconducting coiland adaptive nonlinear control

The very nonlinear nature of the generator and system behaviour following a severe disturbance precludes the use of classical linear control techniques. In this paper, a nonlinear adaptive excitation and a thyristor-controlled superconducting magnetic energy storage (SMES) unit is proposed to enhance the transient stability of a power system with unknown or varying parameters like equivalent reactances of the transmission lines. The SMES unit is located near the generator bus terminal in a power system. A nonlinear feedback control law is found which linearizes and decouples the power system. An adaptive control law is used to design the controller for the generator excitation and SMES system. Simulation results demonstrate that the proposed controller can ensure transient stability of a single-machine-infinite-bus system under a large sudden fault which may occur near the generator bus terminal     

A developed control strategy for mitigating wind power generation transients using superconducting magnetic energy storage with reactive power support

The fast variations of wind speed during extreme wind gusts result in fluctuations in both generated power and the voltage of power systems connected to wind energy conversion system (WECS). This paper presents a control strategy which has been tested out using two scenarios of wind gusts. The strategy is based on active and reactive powers controls of superconducting magnetic energy storage (SMES). The WECS includes squirrel cage induction generator (SCIG) with shunt connected capacitor bank to improve the power factor. The SMES system consists of step down transformer, power conditioning unit, DC–DC chopper, and large inductance superconducting coil. The WECS and SMES are connected at the point of common coupling (PCC). Fuzzy logic controller (FLC) is used with the DC–DC chopper to control the power transfer between the grid and SMES coil. The FLC is designed so that the SMES can absorb/deliver active power from/to the power system. Moreover, reactive power is controlled to regulate the voltage profile of PCC. Two inputs are applied to the FLC; the wind speed and SMES current to control the amount active and reactive power generated by SMES. The proposed strategy is simulated in MATLAB/Simulink®. The proposed control strategy of SMES is robust, as it successfully controlled the PCC voltage, active and reactive powers during normal wind speeds and for different scenarios of wind gusts. The PCC voltage was regulated at 1.0 pu for the two studied scenarios of wind gusts. The fluctuation ranges of real power delivered to the grid were decreased by 53.1% for Scenario #1 and 56.53% for Scenario #2. The average reactive power supplied by the grid to the wind farm were decreased by 27.45% for Scenario #1 and 31.13% for Scenario #2.     

基于可控超导储能的波动负载补偿

提出了一种应用可控超导储能(SMES)装置对波动负载进行补偿的方法。它可以使电网输入的有功功率保持恒定,同时对负载的无功功率进行补偿以提高功率因数。为了有效地进行功率控制,SMES装置的变流器采用电流源型的拓扑结构并与负载并联连接,同时采用闭环控制方法以提高系统的动态性能。为减小交流电流谐波成分,采用了优化脉宽调制开关策略。最后给出了一套20kJ／15kW SMES装置的仿真和实验结果。     

Ant Colony Optimized Fuzzy Control Solution for Frequency Oscillation Suppression

This paper presents a novel approach in addressing a critical power system issue, i.e., automatic generation control (AGC) in a smart grid scenario. It proposes the design and implementation of an optimized fuzzy logic controller (FLC) for AGC of interconnected power network. There are three different sources of power generation considered in the two-area interconnected model of power system network. First area is equipped with a single reheat thermal unit and a superconducting magnetic energy storage (SMES) unit, while another area has a hydro-unit with SMES. A multi-stage optimization strategy for the optimal solution of FLC for tie-line and frequency oscillation suppression is proposed in this paper using an ant colony optimization technique. The optimization of FLC is carried out in four different stages. The first stage is the optimization of range of input and output variables; the second stage is the optimization of membership function; the third and fourth stages are the optimization for rule base and rule weight optimization, respectively. The performance of the proposed controller is also compared with another control approaches to stabilize P_tie-line and Δf oscillations; these are the Ziegler–Nichols-tuned proportional–integral–derivative (PID) controller and genetic algorithm optimized PID controller. A comprehensive analysis of the traditional techniques and proposed techniques is presented on the basis of major dynamic performance parameters, i.e., settling time and peak overshoot.     

Power oscillation damping by superconducting magnetic energy (SMES) storage unit

With the increase in the size and capacity of electric power systems and the growth of widespread interconnections, the problem of power oscillations due to the reduced system damping has become increasingly serious. Since a Superconducting Magnetic Energy Storage (SMES) unit with a self-commutated converter is capable of controlling both the active (P) and reactive (Q) power simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper describes the effects of SMES control on the damping of power oscillations. By examining the case of a single generator connected to an infinite bus through both theoretical analyses and experimental tests (performed with a SMES unit with maximum stored energy of 16 kJ and an artificial model system), the difference in the effects between P and Q control of SMES is clarified as follows:

• 1 In the case of P control, as the SMES unit is placed closer to the terminal of the generator, the power oscillations will decay more rapidly.
• 2 In the case of Q control, it is most effective to install the SMES unit near the midpoint of the system.
• 3 By comparing the P control with Q control, the former is more effective than the latter based on the conditions that the SMES unit location and the control gain are the same.

     

超导储能单元在并网型风力发电系统的应用

风力发电系统发展的趋势是将风力发电机组直接与高压电网相连（简称并网型风力发电系统）。但风速变化造成风力涡轮机械功率变化,会使发电机输出的有功和无功产生波动,从而使电网的电能质量下降。该文提出使用超导储能SMES（super conducting magnetic energy storage system）单元使风力发电机组输出的电压和频率稳定。文中详细介绍了SEMS的调节原理及其最优控制方法,建立了SEMS模型和加入SMES后系统的线性化仿真模型,采用基因算法求最优反馈矩阵,并借助MATLAB软件包设计控制器,仿真结果表明SMES单元对并网型风力发电系统中风力发电机的输出稳定具有极大的改善作用。     

基于超导储能系统的风电场功率控制系统设计

风电场输出功率的波动性和间歇性会给电网带来不利的影响。为了降低风电场并网对电能质量的影响,文中阐述了一种基于超导储能系统的抑制风电场功率波动的间接控制方法。利用超导储能系统的四象限功率运行能力来补偿风电场输出的有功和无功功率波动,并抑制由此产生的电网电压波动;通过合理设计超导储能系统功率调节器的带宽来优化储能量。通过对风电场连接于弱电网的仿真,验证了所提出的功率控制策略的有效性。     

基于混合高温超导储能系统的电网动态功率补偿策略与试验

为实现高温超导储能系统(SMES)对电网功率波动的动态补偿,采用第1代铋系和第2代钇钡铜氧高温超导材料,设计并构建了过冷液氮温区运行、千焦级容量的混合高温超导储能系统。应用数字信号处理器和微控制器的双处理器形式,设计了LCL滤波的电压型SMES变流器的功率控制系统电路,基于空间矢量脉冲调制法(SVPWM),提出了SMES变流器对系统功率补偿的控制方法,并进行控制软件编程,实现对并网侧功率的动态监测和补偿策略的实时计算。最后应用SMES在一条200km输电线路上进行并网动模试验,针对电网负荷变化产生的功率波动状态,实现了毫秒级内对电力系统的快速功率输出和波动抑制,验证了超导储能系统对电网瞬时功率补偿策略和功率补偿变流装置的有效性。     

基于模糊逻辑的有源电力滤波器直接功率控制

基于模糊逻辑的直接功率控制方法用于并联型有源滤波器,有利于消除非线性负载产生的谐波与无功功率补偿。该方法根据瞬时功率理论将瞬时有功功率和无功功率差值作为模糊控制变量,由模糊规则产生开关状态信号,省去功率滞环比较器,不使用传统的预置开关表。仿真和试验表明,该控制方法能够实现网侧单位功率因数、直流侧电压接近参考值,电能质量得到优化。