Robust SMES controller design for stabilization of inter-area oscillation considering coil size and system uncertainties

It is well known that the superconducting magnetic energy storage (SMES) is able to quickly exchange active and reactive power with the power system. The SMES is expected to be the smart storage device for power system stabilization. Although the stabilizing effect of SMES is significant, the SMES is quite costly. Particularly, the superconducting magnetic coil size which is the essence of the SMES, must be carefully selected. On the other hand, various generation and load changes, unpredictable network structure, etc., cause system uncertainties. The power controller of SMES which is designed without considering such uncertainties, may not tolerate and loses stabilizing effect. To overcome these problems, this paper proposes the new design of robust SMES controller taking coil size and system uncertainties into account. The structure of the active and reactive power controllers is the 1st-order lead-lag compensator. No need for the exact mathematical representation, system uncertainties are modeled by the inverse input multiplicative perturbation. Without the difficulty of the trade-off of damping performance and robustness, the optimization problem of control parameters is formulated. The particle swarm optimization is used for solving the optimal parameters at each coil size automatically. Based on the normalized integral square error index and the consideration of coil current constraint, the robust SMES with the smallest coil size which still provides the satisfactory stabilizing effect, can be achieved. Simulation studies in the two-area four-machine interconnected power system show the superior robustness of the proposed robust SMES with the smallest coil size under various operating conditions over the non-robust SMES with large coil size.     

Extremal harmonic active control of power for a monocylinder hybrid powertrain

This article presents a real-life application for the extremal harmonic active control of power [1] applied on a hybrid engine setup. The active control was adapted for a hybrid powertrain constituted of a one-cylinder diesel engine coupled with a permanent magnet synchronous machine. The problem was formulated in the harmonic domain and the control objective was to extremalize energetic criterions. Three criterions were considered: minimizing the speed ripple of the engine, maximizing the mechanical reactive power (mechanical impedance adaptation) and maximizing the active electric power for energy harvesting. The results show that, for the first and second orders of the ripple, speed oscillations can be completely cancelled and reactive power and active power can be optimized on-line. The implicit extremal controller converged rapidly, remaining stable even when the mean engine speed changed abruptly. These results confirm the robustness and the applicability of the extremal harmonic active control for industrial applications.     

Improving robustness of active noise control in ducts

A robust active noise controller (ANC) is proposed here for finite ducts. While the H(infinity) control theory provides theoretical ground and numerical algorithms to design robust controllers, it is important for an engineer to design and formulate a robust controller so that the objective is more achievable and the H(infinity) constraints less restrictive without sacrificing robustness. A new robust ANC is designed this way with an extra actuator to improve achievable performance and introduce more degrees of freedom to controller parameters. The new strategy relaxes H(infinity) constraints without sacrificing robustness and enables the ANC to tolerate a wide variety of errors and uncertainties including truncation errors between a finite model and an infinite field. Theoretical analysis, numerical examples, and experimental results are presented to demonstrate the improved performance of the proposed ANC when subject to a certain level of uncertainties in a duct.     

Hierarchical distributed stabilization of power networks

Large fluctuation of electric power due to high penetration of renewable energy sources such as photovoltaic and wind power generation increases the risk to make the whole power network system unstable. The conventional frequency control called load frequency control is based on PID (proportional-integral-derivative) control or more advanced centralized and decentralized/distributed control. If we could more effectively use information on the state of the other neighbor generators, we can expect to make the whole system more robust against the large frequency fluctuation. This paper proposes a fundamental framework towards the design of hierarchical distributed stabilizing controllers for a network of power generators and loads. This novel type of distributed controller, composed of a global controller and a set of local controllers, takes into account the effect of the interaction among the generators and loads to improve robustness for the variation of locally stabilizing controllers.     

电力系统混沌振荡的等效快速终端模糊滑模控制

电力系统混沌振荡被认为是大型互联电力系统停电事故的主要原因, 本文通过相图、 李雅普诺夫指数图和时域波形图分析了二阶电力系统混沌振荡的动力学行为, 并提出了等效快速终端模糊滑模控制来抑制电力系统混沌振荡, 使其恢复到同步运行状态. 仿真结果表明, 所提出的控制方案不仅具有较快的收敛速度, 而且能够柔化控制信号, 减少控制能量, 并且能有效地降低抖振. 关键词： 电力系统混沌振荡 等效滑模控制 模糊滑模控制 快速终端滑模控制     

Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

This paper investigates how to address the chaos problem in a permanent magnet synchronous generator(PMSG)in a wind turbine system.Predictive control approach is proposed to suppress chaotic behavior and make operating stable;the advantage of this method is that it can only be applied to one state of the wind turbine system.The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation.Moreover,some simulation results are included to visualize the effectiveness and robustness of the proposed method.     

Robust fuzzy control for chaotic dynamics in Lorenz systems with uncertainties

This paper deals with the robust fuzzy control for chaotic systems in the presence of parametric uncertainties. An uncertain Takagi--Sugeno fuzzy model for a Lorenz chaotic system is first constructed. Then a robust fuzzy state feedback control scheme ensures the control for stable operations under bounded parametric uncertainties. For a chaotic system with known uncertainty bounds, a robust fuzzy regulator is designed by choosing the control parameters satisfying the linear matrix inequality. To verify the validity and effectiveness of the proposed controller design method, an analysis technique is suggested and applied to the control of an uncertain Lorenz chaotic system.     

Actuator saturation control of uncertain structures with input time delay

This paper presents a robust saturation control approach for active vibration attenuation of building structures involving parameter uncertainties and input time delay. The parameter uncertainties are described in both polytopic and norm-bounded forms and represent the variations of floor masses, stiffnesses and damping coefficients. The input time delay can be time-varying within a known bound. In terms of the feasibility of certain delay-dependent linear matrix inequalities (LMIs), a state feedback controller can be designed to guarantee the robust stability and performance of the closed-loop system in the presence of parameter uncertainties, actuator saturation, and input time delay. The effectiveness of the proposed approach is investigated by numerical simulations on the vibration control of a three-storey building structure subject to seismic excitation. It is validated that the designed robust saturation controller can effectively suppress the structural vibration and keep the system stability when there are parameter uncertainties and input time delay.     

Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems

The centrifugal flywheel governor (CFG) is a mechanical device that automatically controls the speed of an engine and avoids the damage caused by sudden change of load torque. It has been shown that this system exhibits very rich and complex dynamics such as chaos. This paper investigates the problem of robust finite-time synchronization of non-autonomous chaotic CFGs. The effects of unknown parameters, model uncertainties and external disturbances are fully taken into account. First, it is assumed that the parameters of both master and slave CFGs have the same value and a suitable adaptive finite-time controller is designed. Second, two CFGs are synchronized with the parameters of different values via a robust adaptive finite-time control approach. Finally, some numerical simulations are used to demonstrate the effectiveness and robustness of the proposed finite-time controllers.     

Adaptive robust control of chaotic oscillations in power system with excitation limits

With system parameters falling into a certain area, power system with excitation limits experiences complicated chaotic oscillations which threaten the secure and stable operation of power system. In this paper, to control these unwanted chaotic oscillations, a straightforward adaptive chaos controller based on Lyapunov asymptotical stability theory is designed. Since the presented controller does not need to change the controlled system structure and not to use any information of system except the system state variables, the designed controller is simple and desirable. Simulation results show that the proposed control law is very effective. This work is helpful to maintain the power system＇s security operation.[第一段]     

Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems

The centrifugal flywheel governor(CFG) is a mechanical device that automatically controls the speed of an engine and avoids the damage caused by sudden change of load torque.It has been shown that this system exhibits very rich and complex dynamics such as chaos.This paper investigates the problem of robust finite-time synchronization of non-autonomous chaotic CFGs.The effects of unknown parameters,model uncertainties and external disturbances are fully taken into account.First,it is assumed that the parameters of both master and slave CFGs have the same value and a suitable adaptive finite-time controller is designed.Second,two CFGs are synchronized with the parameters of different values via a robust adaptive finite-time control approach.Finally,some numerical simulations are used to demonstrate the effectiveness and robustness of the proposed finite-time controllers.     

基于继电特性函数的互联电力系统混沌控制

电力系统中的混沌振荡对整个互联电网具有极大危害.本文利用Lyapunov指数、分岔图、相平面图和功率谱等分析一个简单互联电力系统的动力学行为,研究电力系统对电磁功率扰动幅值的敏感性.同时,提出一种基于继电特性函数的准滑动模态控制方法,对系统进行混沌振荡抑制,使系统快速平滑地到达控制目标.实验表明,该方法不仅能够缩短控制时间,减少因参数过大带来的系统冲击,而且对高频抖动也有很好的抑制作用,具有较强的鲁棒性.     

考虑模型不确定性和时延的静止无功补偿器自适应滑膜控制器设计

静止无功补偿器(static var compensator,SVC)不仅可以为电力系统提供无功支撑、稳定电压,其附加控制还可以有效提高系统暂态稳定性,但SVC模型参数的不确定性以及广域测量信号时延等外部干扰给附加控制器的设计带来很大的难度.提出了一种基于自适应滑模变结构理论的SVC鲁棒控制器设计方法,所设计控制器能有效提高系统暂态稳定性,并且其对于模型不确定性以及时延有较好的鲁棒性.首先根据区域惯量中心的运动方程建立了包含SVC的电力系统模型;然后将滑模变结构理论应用于电力系统模型中,求得SVC附加控制律,并通过自适应律优化控制器参数;最后通过四机两区域系统以及IEEE9节点系统对SVC控制器效果进行了仿真验证.结果表明,SVC自适应滑模控制器可以有效提升系统暂态稳定性,并且其性能优于传统的线性控制方法.     

Synthesis of a robust broadband duct ANC system using convex programming approach

A robust active controller using spatially feedforward structure is proposed for broadband attenuation of noise in ducts. To meet the requirements of performance and robust stability in the presence of plant uncertainties, an H2 cost function and an H(infinity) constrain are employed in the synthesis of the controller. The design is then converted into a convex programming problem using Q-parametrization and frequency discretization. An optimal controller that satisfies the quadratic cost functions and linear inequality constraints can be found by sequential quadratic programming. The optimal controller was implemented via a digital signal processor (DSP) and verified by experiments. Experiment results showed that the system attained 16.5 dB maximal attenuation and 5.9 dB total attenuation in the frequency band 200-600 Hz.     

参数不确定统一混沌系统的鲁棒分数阶比例-微分控制

针对含参数不确定的整数阶统一混沌系统, 提出一种鲁棒分数阶比例-微分(PD^μ)控制. 通过变换将受控统一混沌系统转换成等效被控对象及其等效控制器. 针对等效被控对象, 基于一种改进Monje-Vinagre方法并考虑到求解性能约束方程组的复杂度, 设计了鲁棒PD^μ控制器. 通过基于最小相角边界传递函数和最大增益边界传递函数的设计约束来保证受控统一混沌系统对参数不确定性的鲁棒性能. 数值仿真验证了所提出方法的有效性.     

A novel transient rotor current control scheme of a doubly-fed induction generator equipped with superconducting magnetic energy storage for voltage and frequency support

A novel transient rotor current control scheme is proposed in this paper for a doubly-fed induction generator(DFIG)equipped with a superconducting magnetic energy storage(SMES) device to enhance its transient voltage and frequency support capacity during grid faults. The SMES connected to the DC-link capacitor of the DFIG is controlled to regulate the transient dc-link voltage so that the whole capacity of the grid side converter(GSC) is dedicated to injecting reactive power to the grid for the transient voltage support. However, the rotor-side converter(RSC) has different control tasks for different periods of the grid fault. Firstly, for Period I, the RSC injects the demagnetizing current to ensure the controllability of the rotor voltage. Then, since the dc stator flux degenerates rapidly in Period II, the required demagnetizing current is low in Period II and the RSC uses the spare capacity to additionally generate the reactive(priority) and active current so that the transient voltage capability is corroborated and the DFIG also positively responds to the system frequency dynamic at the earliest time. Finally, a small amount of demagnetizing current is provided after the fault clearance. Most of the RSC capacity is used to inject the active current to further support the frequency recovery of the system. Simulations are carried out on a simple power system with a wind farm. Comparisons with other commonly used control methods are performed to validate the proposed control method.     

直驱型永磁同步风力发电机组中混沌运动的反步自适应控制

以直驱型永磁同步风力发电机为研究对象, 推导了发电机在参数不确定以及风速扰动情况下的数学模型,验证了系统在某些参数及工作条件下会呈现出混沌属性. 并提出了直驱型永磁同步风力发电机混沌运动下的基于反步自适应控制算法,并对其进行了仿真, 仿真结果表明,所提出的算法对于具有参数不确定以及风速干扰的直驱型风力发电系统具有较好的鲁棒性. 关键词： 风力发电 直驱型永磁同步风力发电机组 混沌控制 反步自适应控制     

Nonlinear dynamic analysis and surface sliding mode controller based on low pass filter for chaotic oscillation in power system with power disturbance

Chaotic oscillation in the power system often poses a great threat to the stability of the power grid, and the dynamic behaviors of fourth-order power system with power disturbance, which is more in line with the actual situation, are investigated firstly through Lyapunov exponent spectrums and bifurcation diagrams. It is found that the power system with power disturbance has more complex dynamic behaviors and larger domains of chaos. The disturbance terms also result in dynamic behaviors different from those of power system without disturbance, which sometimes brings system motions to period orbits with perturbation-related parameters limited in specific range. Moreover, a dynamic surface sliding mode controller with low pass filter is designed for chaotic suppression, and the relay characteristic function is selected as switching function to inhibit high-frequency chattering. Numerical simulations show that the sliding mode controller owns good effectiveness and strong robustness.     

基于径向小波神经网络的混沌系统鲁棒自适应反演控制

设计了一种具有自适应性和鲁棒性的反演控制律, 实现了对含有系统不确定性的类Rossler系统的控制. 首先通过小波神经网络辨识系统的非线性部分, 将系统转化为含有结构不确定性和参数不确定性的参数化模型; 然后, 对于系统中的参数不确定性, 设计自适应控制律, 在线估计未知参数; 对于系统中的结构不确定性, 设计鲁棒控制律, 使得系统具有鲁棒性. 最后, 通过仿真实现, 验证了以上控制方法的有效性.     

基于粒子群优化的自适应模糊制冷控制算法

为解决空间斯特林制冷机和探测器热负载不确定及存在变化的问题,提出了自适应模糊PID制冷控制。在空间环境中使用的斯特林制冷机参数会随着时间的变化而发生改变,探测器负载也会随着工作模式和工作时间的变化而变化,整个制冷系统涉及的变量多,参数非线性。采用传统的控制方法,在固定的单一条件、环境下得到的控制参数,环境和负载发生变化后容易性能变差甚至不稳定,控制精度和稳定性不能满足使用要求。设计了一种自适应斯特林制冷机控制器,通过综合自适应模糊PID控制的方法,采用粒子群优化算法调整控制参数以减小代价函数。通过仿真和试验验证算法的有效性和鲁棒性。