利用自适应校正设计的同步发电机神经控制器

电力系统是大规模非线性系统,其不确定性、快速动态等特性一直是稳定控制中难以解决的问题。神经网络控制由于具有自组织性、自适应性、容错性等性能,近年来在控制领域取得了很大的发展。文中介绍了一种新型神经控制器,该控制器应用自适应校正设计的原理,选用基于控制网络的启发式动态规划(Action-DependantHeuristicDynamicProgramming),设计中利用控制网络与校正网络交替训练的方法进行控制器的优化,具有结构简单,不依赖于受控系统的优点,并且能够实现在线学习。以单机无穷大系统为例,在Matlab/Simulink环境中对系统不同运行方式进行仿真,将该神经控制器同传统控制器进行对比,结果显示前者能够对系统振荡进行更好的阻尼,并且对不同工况保持稳定一致的控制效果,体现了很强的鲁棒性。     

Dual heuristic programming excitation neurocontrol for generators in a multimachine power system

The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage regulators for excitation control of turbogenerators in a multimachine power system is presented in this paper. The neurocontroller design is based on dual heuristic programming (DHP), a powerful adaptive critic technique. The feedback variables are completely based on local measurements from the generators. Simulations on a three-machine power system demonstrate that DHP-based neurocontrol is much more effective than the conventional proportional-integral-derivative control for improving dynamic performance and stability of the power grid under small and large disturbances. This paper also shows how to design optimal multiple neurocontrollers for nonlinear systems, such as power systems, without having to do continually online training of the neural networks, thus avoiding risks of neural network instability.     

执行依赖启发式动态规划在同步发电机励磁系统中的应用

介绍了一种控制同步发电机励磁系统的新方法,即执行依赖启发式动态规划(ADHDP)对同步发电机励磁电压的自适应控制.执行依赖启发式动态规划是近似动态规划(ADP)的一种算法,ADP利用非线性函数拟合方法逼近动态规划的性能指标函数,以获得最优解或次优解.仿真结果表明,基于执行依赖启发式动态规划算法的励磁控制效果优于传统励磁...     

Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm

In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance by uncertainty of membership function especially when we have to confront with less expert knowledge or unpredicted external disturbances. The corresponding parameters and rule base of type-2 fuzzy logic power system stabilizer are optimally tuned by using differential evolution algorithm for multi-machine power system. Through simulation under different operational conditions, the results demonstrate the effectiveness of the proposed approach for damping the power system electromechanical oscillations.     

Adaptive Power System Stabilizer Design Using Optimal Support Vector Machines Based on Harmony Search Algorithm

Abstract—This article presents the application of support vector machines to adaptive power system stabilizer design in a multi-machine power system based on the harmony search algorithm. Data from a multi-machine power system are the input features of the support vector machines. Support vector machine parameters and power system features are simultaneously optimized by harmony search based on the k-fold cross-validation technique. The proposed algorithm is trained by the optimal support vector machine parameters and optimal power system features. Power system stabilizer parameters produced by the proposed algorithm can be adapted by various operating conditions when the power system operates either inside or outside the training ranges. Simulation studies in the IEEJ Western Japan ten-machine power system demonstrate that the proposed algorithm is far superior to conventional power system stabilizers with fixed parameters and those designed by a robust coupled vibration model under various operating conditions and severe disturbances.     

Robust coordinated design of multiple and multi-type damping controller using differential evolution algorithm

A robust coordination scheme to improve the stability of a power system by optimal design of multiple and multi-type damping controllers is presented in this paper. The controllers considered are power system stabilizer (PSS) and static synchronous series compensator (SSSC)-based controller. Local measurements are provided as input signals to all the controllers. The coordinated design problem is formulated as an optimization problem and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performance of the proposed controllers is evaluated for both single-machine infinite-bus power system and multi-machine power system. Nonlinear simulation results are presented over a wide range of loading conditions and system configurations to show the effectiveness and robustness of the proposed coordinated design approach. It is observed that the proposed controllers provide efficient damping to power system oscillations under a wide range of operating conditions and under various disturbances. Further, simulation results show that, in a multi-machine power system, the modal oscillations are effectively damped by the proposed approach.     

多机电力系统神经网络最优励磁控制器

针对多机电力系统，提出了一种基于辨识的神经网络实时最优控制器(NNOEC)，在所设计的控制器中，神经网络被用来根据系统状态量的变化实时调整最优控制的反馈增益矩阵，使控制器能够适应不同的运行点和干扰种类。并始终提供最优控制输出。针对多机系统中神经网络训练样本不易获得的问题，提出了一种等效的设计方法，并采用非线性最小二乘辨识法对系统参数进行辨识，在辨识的基础上通过线性最优控制理论计算出用于神经网络训练的样本。三机系统中的数字仿真结果表明，所训练出的NNOEC能够适应系统运行方式的大范围变化，在大小扰动下均表现出良好的控制性能。     

Modified vector controlled DFIG windenergy system based on barrier functionadaptive sliding mode control

Increased penetration of wind energy systems has serious concerns on power system stability. In spite of several advantages, doubly fed induction generator (DFIG) based wind energy systems are very sensitive to grid disturbances. DFIG system with conventional vector control is not robust to disturbances as it is based on PI controllers. The objective of this paper is to design a new vector control that is robust to external disturbances. To achieve this, inner current loop of the conventional vector control is replaced with sliding mode control. In order to avoid chattering effect and achieve finite time convergence, the control gains are selected based on positive semi-definite barrier function. The proposed barrier function adaptive sliding mode (BFASMC) is evaluated by testing it on a benchmark multi-machine power system model under various operating conditions. The simulated results show that the proposed method is robust to various disturbances.     

基于非线性规划方法的PSS参数优化设计

在多机系统中,电力系统稳定器的参数配置是一个复杂的非线性优化问题,可以应用先进的现代内点算法求解该优化问题.本文以Anderson3机9节点系统为例,应用现代内点算法来进行PSS参数优化.通过发电机在不同运行方式下(正常、负荷高峰、负荷低谷)的动态性能仿真结果表明:用现代内点算法进行参数优化后的PSS动态性能优于常规方法设计的PSS,具有一定的鲁棒性.     

基于受控微分—代数系统灵敏度分析的紧急控制

基于时域仿真得到的系统受扰轨迹给出了暂稳紧急控制的非线性规划模型，该模型采用一种启发式的功角积分型指标构成稳定约束。通过引入受控非线性微分-代数系统灵敏度分析求出所定义的功角积分型指标对控制变量的梯度后，给出了所建立的暂稳紧急控制非线性规划模型的2种求解方法：近似规划算法和拟贪婪算法。所提出的暂稳紧急控制模型与时域仿真具有同等的模型适应性。对多机系统切机／切负荷暂稳紧急控制的数值仿真表明，该方法是有效的。     

Performance Enhancement of Power System Stabilizer Through Colony of Foraging Ants

In this article, the concept of foraging behavior of a colony of natural ants is used for the optimal design of power system stabilizers. The controller design is formulated as an optimization task and the novel concept is used to derive the controller structure. The proposed approach is applied to the multi-machine test systems. The dynamic performance of the system has been examined under different perturbations and loading conditions. Various performance characteristics of the technique are thoroughly investigated and compared with the genetic algorithm based approach. The comparison shows that the ant colony optimization based technique converges much faster with lesser number of iterations through simple computational steps. It is also shown through extensive simulations that the proposed controller gives an excellent damping performance over different disturbances and wide range of operating conditions.     

基于自适应旋转惯量VSG控制策略光储微网系统

针对光伏储能并网发电系统采用常规虚拟同步机VSG(virtual synchronous generator)控制策略在负荷扰动时系统的稳定性和动态性能欠佳的问题,本文提出一种基于自适应旋转惯量VSG控制策略的光伏储能并网发电系统.在常规VSG控制策略的基础上,利用同步发电机的功角特性曲线及转子角速度振荡周期曲线,分析...     

考虑控制量限幅的发电机非线性分散鲁棒汽门控制

提出了一种冗余控制量情况下考虑控制量限幅的非线性反馈控制方法,这种方法通过在动态过程的任一时间点上求解一个具有不等式约束的最优化问题得到该时刻各控制量值,使实际能够给出的虚拟控制量尽量达到保证系统渐近稳定所需要的虚拟控制量要求。将该方法与引入量测变量的建模方法相结合,设计了可同时考虑高压、中低压缸汽门控制的多机系统非线性分散鲁棒汽门控制器。对一个多机交直流系统的数字仿真表明,所设计的控制器是有效的。     

不确定微分代数系统的多指标非线性鲁棒自适应控制方法

针对含不确定因素的多输入多输出微分代数系统,提出一种多指标非线性鲁棒自适应控制方法(multi-index nonlinear robust adaptive control,MINRAC),并将其应用于汽门开度与发电机励磁的协调控制上。数字仿真表明：在系统参数不确定和存在外部扰动的情况下,该方法能够使得系统的多个指标都运行在期望的工作点上而不发生静态偏移。对于不同类型的扰动,如有功功率阶跃,三相短路,该控制方法都能很好地镇定系统,并且能够消除机端电压偏差。与多指标非线性控制(multi-index nonlinear control,MINC)和多指标非线性鲁棒控制(multi-index nonlinear robust control,MINRC)相比,该文提出的方法能更好地兼顾系统的动静态性能。     

混合交直流电力系统的非线性调制策略

针对大扰动情形，文中提出了一种用于改善多机交直流混合电力系统（有多条直流线路落点于其中）暂态稳定性的非线性控制方法，该方法基于微分几何理论，地直流输电系统等效为两个分别连接在整流侧和逆变侧的变导纳支路，在推导出直流输电系统的等效变导纳与各发电机输出电磁功率间的解析关系后，传统的发电机动态方程可被表示成仿射非线性的形式，因而可应用全局线性化方法来求得其控制变量，本文方法的主要特点在于，所求得的调制功率是一个交流系统状态的自适应和非线性函数，它可通过局部的反馈信号和少量来自其它发电机的信号来实现，文中以一个双馈入直流输电系统为测试对象，给出了所提控制器的设计过程和基于测试系统的仿真结果。     

Multi-machine power system stabilizer design by rule based bacteria foraging

Several power system stabilizers (PSS) connected in number of machines in a multi-machine power systems, pose the problem of appropriate tuning of their parameters so that overall system dynamic stability can be improved in a robust way. Based on the foraging behavior of Escherichia coli bacteria in human intestine, this paper attempts to optimize simultaneously three constants each of several PSS present in a multi-machine power system. The tuning is done taking an objective function that incorporates a multi-operative condition, consisting of nominal and various changed conditions, into it. The convergence with the proposed rule based bacteria foraging (RBBF) optimization technique is superior to the conventional and genetic algorithm (GA) techniques. Robustness of tuning with the proposed method was verified, with transient stability analysis of the system by time domain simulations subjecting the power system to different types of disturbances.     

基于增强连续禁忌算法的PSS参数优化

多机系统中,电力系统稳定器PSS(Power System Stabilizer)的参数配置是一个复杂的非线性优化问题。描述了电力系统模型、PSS模型及参数优化目标函数和约束条件。介绍了增强连续禁忌算法ECTS(Enhanced Continuous Tabu Search)的主要组成部分及算法流程图。并以WSCC3机9节点系统为例进行PSS参数优化,通过发电机在不同方式下(正常、负荷高峰、负荷低谷)的动态性能仿真,结果表明：用ECTS算法参数优化后的PSS动态性能优于常规方法设计的PSS,具有一定的鲁棒性。     

Optimal IPFC signal selection and damping controller design using a novel current injection model in a multi-machine power system

This paper develops a novel approach to model the Interline Power Flow Controller (IPFC) with the purpose of enhancing the power system dynamic stability. The dynamic behavior of the IPFC is modeled using a new and detailed current injection model. On the basis of designing a supplementary damping controller, the effectiveness of the proposed model in robust damping of the oscillations is evaluated. Thus, the problem of attaining the damping controller parameters transmitted into an optimization process which is solved using Particle Swarm Optimization algorithm (PSO). The PSO has a strong and reliable capability to find out the optimistic solution. The optimization procedure is performed in a multi-machine power system and under various operating conditions. Assessment the derived results from the nonlinear time domain simulation and through some performance indices with considering to a severe transient disturbance clearly indicates the major performance of the proposed model and the model based designed controller in improvement the system stability margins. Moreover, to identify the most suitable IPFC control signal, a precise evaluation of the employed indices is accomplished. Numerical results verify the superior stabilization effect of the m₁ (one of the IPFC control signals) in the wide range of operating conditions.     

含风电系统的发用电一体化调度模型

在传统发电调度模式中融入用电调度,为风电等间歇性电源并网提供备用资源、保证电力平衡开辟了一条可行的途径.考虑融入用电激励、可中断负荷、电价响应等用电调度方式,建立了含风电系统的发用电一体化调度模型,采用启发式动态规划算法进行求解.算例分析表明,通过科学决策发用电资源调度,融入用电激励方式能够减少低谷时段风电弃风,提高了...     

Design of a static VAR compensator using model reference adaptive control

A novel approach for the design of a static VAR compensator (SVC) is proposed. The SVC, which comprises a fixed capacitor and a thyristor-controlled inductor, can be used to improve generator damping without deterioration in the voltage profile under severe disturbance conditions. In order to achieve better dynamic performance, a supplementary proportional-integral (PI) controller, of which the parameters are determined by eigenvalue assignment, is incorporated in the static VAR compensator. To further improve the damping characteristics over a wide range of operating conditions, an adaptive controller using model reference adaptive control (MRAC) is also developed. Results from the digital simulation of the system subject to a three-phase fault indicate that the MRAC can provide better dynamic performance than the fixed-gain PI controllers.