基于强化学习算法的静止同步补偿电压控制器

将强化学习算法应用于静止同步补偿(STATCOM)电压控制器,克服了常规STATCOM电压控制器对系统数学模型的依赖性,同时根据来自系统的强化学习信号,采用自适应启发评价算法更新其参数.在控制器中采用局部可测信息量,以确保其可实现性.仿真实验结果表明,基于强化学习算法的STATCOM电压控制器可以在紧急情况下对系统电压进行调节,从而在一定程度上确保了系统的安全稳定运行.     

STATCOM与发电机励磁非线性控制器设计

提出了一种有利于进行控制设计的STATCOM模型.采用直接反馈线性化、零动态原理,设计了STATCOM无功电流与发电机励磁非线性控制器,该控制可以同时满足发电机励磁与STATCOM装设处电压的稳定性.对单机-无穷大系统进行了数字仿真,结果表明该控制器具有很好的实用效果和优越性.     

STATCOM鲁棒非线性控制

讨论了STATCOM的鲁棒非线性控制设计问题。利用直接反馈线性化技术（DFL）把STATCOM非线性模型转换成线性模型,并利用鲁棒控制器的设计方法消除模型中不确定参数的影响。设计过程中只需要不确定参数的边界,所设计控制器简单、有效,并能保证系统在所有参数范围内的渐进稳定性。3母线电力系统的仿真结果表明该控制器在系统具有不确定参数时能取得良好的电压调节性能。     

STATCOM的自适应逆控制方法

为了研究静止同步补偿器STATCOM运行过程中存在的非线性特性对补偿特性的影响，在考虑了电压源型逆变桥中IGBT的通态损耗、开关损耗以及直流侧的电容损耗基础上，建立了基于该逆变桥的STATCOM数学模型，并根据其数学模型的非线性特性，提出了STATCOM的自适应逆控制方法和逆系统模型。根据该模型对STATCOM进行直接控制，并根据系统参数的不可预知以及其时变的特点，对系统模型中的参数在运行过程进行在线识别，并进行了仿真。结果表明，自适应逆控制能够有效地克服运行过程中系统参数的变化对补偿效果的影响，从而提高了控制系统的鲁棒性和装置的控制精确度；给定系统参数的初值准确与否，对装置最终的控制精确度没有影响。该控制方法具有实用性，而且随着处理器计算能力的不断增强该方法存在广泛的应用前帚。     

扩展二级电压的多Agent协调控制

基于多Agent系统的分布式协调机制,研究了发生事故的紧急情况下综合考虑多种类型电压控制器(AVR,SVC,STATCOM)的扩展二级电压协调控制。在应用一种慢相关技术将电力系统划分为多个电压控制区的基础上,提出了多Agent间进行任务协助请求时的选择原则,确定了Agent间的协调机制。以装设2台SVC,2台STATCOM和10台发电机AVR的新英格兰系统为例进行数字仿真,结果验证了该控制方案的有效性和灵活性。     

扩展二级电压的多Agent协调控制

基于多Agent系统的分布式协调机制,研究了发生事故的紧急情况下综合考虑多种类型电压控制器(AVR,SVC,STATCOM)的扩展二级电压协调控制.在应用一种慢相关技术将电力系统划分为多个电压控制区的基础上,提出了多Agent间进行任务协助请求时的选择原则,确定了Agent间的协调机制.以装设2台SVC,2台STATCOM和10台发电机AVR的新英格兰系统为例进行数字仿真,结果验证了该控制方案的有效性和灵活性.     

STATCOM与发电机励磁和汽轮机调门非线性协调滑模控制研究

基于单机无穷大系统,建立了静止同步补偿器(static synchronous compensator,STATCOM)的数学模型,设计了变结构协调控制器.采用直接反馈对系统进行全局线性化,运用变结构控制方法,设计了STATCOM无功电流与发电机励磁、汽轮机调门的非线性滑模协调控制器,可以同时满足发电机励磁、汽机调门与STATCOM装设处电压稳定要求.对单机一无穷大系统进行了数字仿真,结果表明控制器能有效改善系统稳定性.     

一种基于体液免疫原理的电网故障诊断模型设计方法

该文借鉴体液免疫应答原理解决当前电网故障诊断所面临的故障信息不确定性问题。首先,构建了体液免疫应答过程与电网故障诊断过程所涉及的基本量的对应关系。其次,模拟体液免疫抵御抗原入侵的免疫机制和结构,构建了基于体液免疫应答机制的电网故障诊断模型,该诊断模型具有较强的容错能力,不仅可以根据先验知识诊断出已知的故障,而且能够通过系统的连续学习功能诊断未知的故障。最后,通过诊断算例验证了所构建诊断模型的有效性与可行性。     

STATCOM无功电流的鲁棒自适应控制

从器件级、装置级和系统级3个层次讨论电压源型STATCOM的数学建模和控制器设计;提出了一种鲁棒型直接自适应控制算法,以解决STATCOM模型参数未知情况下无功电流的追踪控制问题。在对象系统严格正实性得以验证的基础上,系统地选择了控制器设计参数,并考虑了输入输出噪声对控制系统的影响,从而使控制器具有较好的鲁棒性。数字仿真结果表明,得到的控制器在追踪控制能力和鲁棒特性等方面比PI控制优越。     

静止同步补偿器的双环控制系统设计

静止同步补偿器(STATCOM)的主要功能是支撑节点电压,同时直流侧电容电压稳定也是STATCOM装置安全运行的保证。介绍了STATCOM装置的数学模型和运行原理,提出了一种新的控制策略。采用电流前馈环节加比例积分(PI)调节系统控制直流电容电压,节点电压控制采用PI调节和一定的下垂比例因子组成的自动电压调整控制策略。详细探讨了控制系统的设计方法和过程。仿真以及7.5kV.A物理模型的实验结果表明,能够快速有效地将节点电压控制在允许的范围内波动,直流电容电压得到有效控制,证明了控制系统的正确性和控制器设计的有效性。     

Voltage regulation with STATCOMs: modeling, control and results

This paper presents system modeling and control design for fast load voltage regulation using static compensators (STATCOMs). The modeling strategy gives a clear representation of load voltage magnitude and STATCOM reactive current on an instantaneous basis. The particular coordinate transformation employed here also facilitates extraction of linearized system dynamics in conjunction with circuit simulators. It is rigorously shown that the control problem of load voltage regulation using reactive current is nonminimum phase. Linear and nonlinear controllers for the regulation problem are designed and compared via simulation results. Internal dynamics of the STATCOM are modeled using the same strategy. Lyapunov based adaptive controllers are designed for controlling the STATCOM reactive current while maintaining its dc bus voltage. Simulation results of the controlled STATCOM integrated with the load bus voltage controller are presented to show efficacy of the modeling and control design.     

Integrated PLC-fuzzy PID Simulink implemented AVR system

Improving the transient response of power generation systems using automation control in a precise manner is the key issue. We design a fuzzy proportional integral derivative (PID) controller using Matlab and programmable logic controllers (PLCs) for a set point voltage control problem in the automatic voltage regulator (AVR) system. The controller objective is to maintain the terminal voltage all the time under any loads and operational conditions by attaining to the desired range via the regulation of the generator exciter voltage. The main voltage control system uses PLCs to implement the AVR action. The proposed fuzzy controller combines the genetic algorithm (GA), radial-basis function network (RBF-NN) identification and fuzzy logic control to determine the optimal PID controller parameters in AVR system. The RBF tuning for various operating conditions is further employed to develop the rule base of the Sugeno fuzzy system. The fuzzy PID controller (GNFPID) is further designed to transfer in PLCs (STEP 75.5) for implementing the AVR system with improved system response. An inherent interaction between two generator terminal voltage control and excitation current is revealed. The GNFPID controller configures the control signal based on interaction and there by reduces the voltage error and the oscillation in the terminal voltage control process. We achieve an excellent voltage control performance by testing the proposed fuzzy PID controller on a practical AVR system in synchronous generator for improve the transient response.     

Optimal controllers designs for automatic reactive power control in an isolated wind-diesel hybrid power system

The paper presents the bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) algorithm based robust controllers for voltage deviations due to the variation of reactive power in an isolated wind-diesel hybrid power system. The isolated wind-diesel system consists of wind energy conversion system (WECS) utilizing a permanent magnet induction generator (PMIG). Further, a synchronous generator (SG) is used with the diesel engine set for power generation. The mismatch between generated and consumed reactive power in the system causes voltage fluctuations, which will occur at generator terminals. These oscillations further causes reduction in the stability and quality of the power supply. The static synchronous compensator (STATCOM) and an automatic voltage regulator (AVR) are used to suppress voltage fluctuations in an isolated wind-diesel hybrid power system. The STATCOM is used as a reactive power compensator and the AVR is used to keep the terminal voltage constant for the synchronous generator. Both STATCOM and AVR are having proportional and integral (PI) controllers with single input. In modeling for the system, a normalized co-prime factorization is applied to show the possible unstructured uncertainties in the power system such as variation of system parameters and generating and loading conditions. The performance and robust stability conditions of the control system are formulated as the optimization problem, which is based on the Hα loop shaping. BFOA and PSO algorithms are implemented to solve this optimization problem and to achieve PI control parameters of STATCOM and AVR simultaneously. In order to show the efficiency of the proposed controllers, the performance of the proposed controllers is compared with the performance of the conventional controller and genetic algorithm (GA) based PI controllers for the same wind-diesel system. The dynamic responses of the system for four different small-disturbance case studies has been carried out in MATLAB environment.     

Particle Swarm Optimization-based Superconducting Magnetic Energy Storage for Low-voltage Ride-through Capability Enhancement in Wind Energy Conversion System

Abstract— This article presents a novel application of the particle swarm optimization technique to optimally design all the proportional–integral controllers required to control both the real and reactive powers of the superconducting magnetic energy storage unit for enhancing the low-voltage ride-through capability of a grid-connected wind farm. The control strategy of the superconducting magnetic energy storage system is based on a sinusoidal pulse-width modulation voltage source converter and proportional–integral-controlled DC-DC converter. Control of the voltage source converter depends on the cascaded proportional–integral control scheme. All proportional–integral controllers in the superconducting magnetic energy storage system are optimally designed by the particle swarm optimization technique. The statistical response surface methodology is used to build the mathematical model of the voltage responses at the point of common coupling in terms of the proportional–integral controller parameters. The effectiveness of the proportional–integral-controlled superconducting magnetic energy storage optimized by the proposed particle swarm optimization technique is then compared to that optimized by a genetic algorithm technique, taking into consideration symmetrical and unsymmetrical fault conditions. A two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The systemic design approach is demonstrated in determining the controller parameters of the superconducting magnetic energy storage unit, and its effectiveness is validated in augmenting the low-voltage ride-through of a grid-connected wind farm.     

基于系统辨识建模的微网二次电压频率控制器参数设计方法

在采用由下垂或者虚拟同步机控制的逆变器构建的微网系统中,二次电压频率调节器参数优化是提高微网电压频率性能的关键。进行电压频率参数优化分析的前提是获取微网电压频率响应模型,但是由于微网系统结构复杂多样,系统内微源和负荷种类繁多,以及商业化电源广泛使用造成的电源模型难以获得等原因,给微网机理建模带来了很多困难。为解决上述问题,通过建立微网系统公共连接点电压频率响应模型结构,利用在微网中采样的运行数据以及系统辨识方法对模型中传递函数进行辨识,并利用辨识得到的模型对微网系统二次电压频率控制器进行参数优化。所提方法不仅可以在微网内部结构以及电源模型未知的情况下对微网进行建模,而且所建模型阶次低,便于调节器参数设计使用。最后,在微网实验平台上对所提方法的有效性进行了实验验证。     

基于模糊神经解耦控制的双馈水轮发电机系统仿真

双馈水轮发电机系统是一个涉及水力、水轮机和发电机的综合复杂系统。针对系统具有多变量、非线性、强耦合和参数不确定性的特点，本文提出了一种两级串联结构的自适应模糊神经网络解耦控制策略，前级为基于智能权函数规则的自调整模糊控制器，后级为基于动态耦合特性的自适应神经网络解耦控制器，并从理论上证明了学习算法的收敛性。为了验证所提出控制策略的有效性和正确性，本文对双馈水轮发电机系统在水力、水轮机和发电机参数变化时的鲁棒性分别进行了仿真研究。与常规PID控制的仿真结果比较表明，提出的解耦控制策略能较好地克服参数变化和对象模型结构变化对运行性能的影响，具有鲁棒性好，解耦能力强的优点。     

An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response

Subsequent commutation failure (SCF) can be easily generated during the frst commutation failure (CF) recovery process in a line-commutated converter-based high voltage direct-current system. SCF poses a signifcant threat to the safe and stable operation of power systems, and accurate prediction of CF is thus important. However, SCF is afected by the operating characteristics of the main circuit and the coupling efects of sequential control response in the inverter station. These are difcult to predict accurately. In this paper, a new SCF prediction method considering the control response is proposed based on the physical principle of SCF. The time sequence and switching conditions of the controllers at diferent stages of the frst CF recovery process are described, and the corresponding equations of commutation voltage afected by diferent controllers are derived. The calculation method of the SCF threshold voltage is proposed, and the prediction method is established. Simulations show that the proposed method can predict SCF accurately and provide useful tools to suppress SCF     

Adaptive control design for VSC-HVDC systems based on backstepping method

An adaptive control design is proposed to improve dynamic performances of voltage source converter high voltage direct current (VSC-HVDC) systems. The adaptive controller design for nonlinear characteristics of VSC-HVDC systems, which is based on backstepping method, considers parameters uncertainties. For an original high-order system, the final control laws can be derived step by step through suitable Lyapunov functions. Thus, the design process is not complex. The effectiveness of the proposed adaptive controllers is demonstrated through digital simulation studies on a VSC-HVDC power system, using the PSCAD/EMTDC software package. The simulation results show that the controllers contribute significantly toward improving the dynamic behavior of the VSC-HVDC system under a wide range of operating conditions.