Optimal robust adaptive fuzzy synergetic power system stabilizer design

A new particle swarm optimized robust indirect adaptive power system stabilizer is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use of a chatter free continuous control law which makes the controller easy to implement. In addition the controller parameters are optimized using PSO approach. Simulation of severe operating conditions of a power system is conducted to validate the effectiveness of the proposed approach while stability is guaranteed via Lyapunov synthesis.     

利用LMI技术设计鲁棒电力系统稳定器

传统的H∞控制理论在电力系统中的应用有种种限制,线性矩阵不等式(LMI)技术为多目标控制器的综合提供了新的途径.借鉴有极点区域配置约束的混合H∞/H2问题的LMI解法,设计了多目标H∞电力系统稳定器用于阻尼低频振荡.特征根计算与仿真分析表明,该控制器可在较大范围运行条件情况下向系统提供足够的阻尼.     

利用LMI技术设计鲁棒电力系统稳定器

传统的H∞控制理论在电力系统中的应用有种种限制,线性矩阵不等式 (LMI)技术为多目标控制器的综合提供了新的途径。借鉴有极点区域配置约束的混合H∞ /H2 问题的LMI解法,设计了多目标H∞电力系统稳定器用于阻尼低频振荡。特征根计算与仿真分析表明,该控制器可在较大范围运行条件情况下向系统提供足够的阻尼。     

A new stabilizer design technique for multimachine power systems

A simple and systematic procedure for decentralized stabilizer design for multimachine systems is presented in this paper. The procedure first selects the most effective location of a stabilizer according to a machine stability index. The parameters of the stabilizer are then determined by a decentralized feedback control scheme. This process is carried out for one stabilizer at a time. The resultant overall improvement of the system stability, measured by a system stability index, is used to decide how many stabilizers are required for the system. The proposed technique is illustrated by a test system. Both eigenvalue analysis and nonlinear simulation are performed to investigate the effectiveness of the technique.     

Design of a robust power system stabilizer using fuzzy logic for a multi-machine power system

This paper presents a design procedure for a fuzzy logic based power system stabilizer (FPSS) and investigates the robustness of the FPSS for a multi-machine power system. Speed deviation of synchronous generator and its derivative are chosen as the input signals to the FPSS. A two area, five generator power system is used to illustrate the robustness of the FPSS. A normalized sum-squared deviation (NSSD) index is used for designing the FPSS and demonstrating its robustness. Nonlinear simulation tests for different disturbances and their results are discussed.     

New approach to power system stabilizer design

A generalized method for the design of excitation control or a power system stabilizer (PSS) based on complex frequency is described. The method selects PSS parameters such that exact assignment of eigenvalues associated with the mechanical modes of oscillation to desired locations is achieved. Numerical examples are used to illustrate the concepts of the proposed new technique.     

电力系统稳定器参数优化的研究

电力系统稳定器(PSS)的性能受其参数影响很大,如何对其参数进行协调优化是一个值得深入研究的问题.基于单机无穷大系统和4机2区域系统模型,通过采用 SFPSO算法对电力系统稳定器进行参数的协调优化,以抑制低频振荡.随机聚焦粒子群算法SFPSO(Stochastic focusing particle swarm optimization)是一种应用于连续空间的、具有较好的全局搜索能力和寻优速度的改进粒子群算法(PSO).通过仿真测试以及不同算法优化结果的对比,结果表明,利用该方法设计的PSS,在不同的干扰下都具有良好的性能,对系统的稳定性提升有较大帮助.     

电力系统稳定器参数优化的研究

电力系统稳定器(PSS)的性能受其参数影响很大,如何对其参数进行协调优化是一个值得深入研究的问题。基于单机无穷大系统和4机2区域系统模型,通过采用 SFPSO算法对电力系统稳定器进行参数的协调优化,以抑制低频振荡。随机聚焦粒子群算法SFPSO（Stochastic focusing particle swarm optimization）是一种应用于连续空间的、具有较好的全局搜索能力和寻优速度的改进粒子群算法（PSO）。通过仿真测试以及不同算法优化结果的对比,结果表明,利用该方法设计的PSS,在不同的干扰下都具有良好的性能,对系统的稳定性提升有较大帮助。     

基于社会学习的粒子群优化算法的电力系统稳定器参数协调优化设计

对于电力系统稳定器(PSS)参数优化整定的问题,为了更好地寻找最优参数,本文将社会学习机制引入到粒子群优化算法中,将社会学习粒子群优化算法(SLPSO)应用于PSS参数的优化整定中,相比于传统优化算法,本文算法优化P SS参数具有更好的动态自适应性,同时不易陷入局部最优,能够较快地寻找到全局最优值.通过四机两区的仿真算...     

基于粒子群优化算法的PSS参数优化

粒子群算法(PSO-ω)是一种应用于连续空间的、具有较好的全局搜索能力和寻优速度的群体智能优化算法.基于单机无穷大系统模型,通过采用PSO-ω算法对电力系统稳定器(PSS)进行参数优化,以抑制低频振荡.该方法是以最优控制原理为基础,综合考虑PSS与励磁系统的性能,将PSS参数优化协调转化为带有不等式约束的优化问题,控制目标为系统输出按照最小误差跟踪给定值的能力(ITAE准则).用Matlab软件进行仿真,结果表明,利用该方法设计的PSS,它的稳定性有了较大的提高.     

Chaotic ant swarm optimization for fuzzy-based tuning of power system stabilizer

In this paper, chaotic ant swarm optimization (CASO) is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). This algorithm explores the chaotic and self-organization behavior of ants in the foraging process. A novel concept, like craziness, is introduced in the CASO to achieve improved performance of the algorithm. While comparing CASO with either particle swarm optimization or genetic algorithm, it is revealed that CASO is more effective than the others in finding the optimal transient performance of a PSS and automatic voltage regulator equipped single-machine-infinite-bus system. Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. It is revealed that the transient performance of dual-input PSS is better than single-input PSS. It is, further, explored that among dual-input PSSs, PSS3B offers superior transient performance. Takagi Sugeno fuzzy logic (SFL) based approach is adopted for on-line, off-nominal operating conditions. On real time measurements of system operating conditions, SFL adaptively and very fast yields on-line, off-nominal optimal stabilizer variables.     

采用广域测量信号的PSS参数优化设计

为了解决传统的电力系统稳定器PSS(Power System Stabilizer)因局限于反馈本地信号而不能很好地抑制区域模式的问题,针对区域模式装设引入广域测量信号的PSS,针对地区模式装设引入本地信号的PSS。根据参与因子确定PSS装设地点,然后应用遗传算法对其参数进行协调。由于PSS反馈远方信号,设计时考虑了通信延迟的影响。算例表明,提出的方案能够较好地抑制低频振荡。     

An adaptive fuzzy logic power system stabilizer

The paper presents an adaptive fuzzy logic power system stabilizer (PSS) design for damping oscillatory electromechanical modes of oscillations and enhancing the first-swing synchronous stability margins. The novel design utilizes a multivariable damping signal vector consisting of machine speed deviation, rate of speed deviation, and voltage deviation. The design is based on a multizonal PID structure and fuzzy logic variable-gain scheduling to optimize the damping action. The fuzzy logic PSS is proposed for use in parallel with the conventional analog type PSS with added simple switching criteria. The two PSS blocks can be allowed independent, sequential, and/or combined operation with different effective stabilizing weighting. The paper investigates an individual conventional PSS, a rule based fuzzy PSS, and hybrid operation. The parallel operation of a conventional PSS and a fuzzy logic one provides optimal sharing of the damping action under small- as well as large-scale generation-load mismatch or variations in external network topology due to fault or switching conditions.     

基于粒子群优化算法的电力系统稳定器设计

基于单机无穷大系统模型,用粒子群优化算法(PSO)对发电机电力系统稳定器(PSS)进行参数优化,来抑制低频振荡.介绍了基本的粒子群优化算法的原理,并用改进的带约束的粒子群优化算法优化PSS的参数,将PSS的整个设计过程转化为一组参数进行寻优的过程,提高了多参数寻优的效率.用Matlab仿真软件进行仿真,仿真结果表明,利用该方法设计的PSS,它的小信号稳定性有了较大的提高.     

基于粒子群优化算法的电力系统稳定器设计

基于单机无穷大系统模型,用粒子群优化算法（PSO）对发电机电力系统稳定器(PSS)进行参数优化,来抑制低频振荡。介绍了基本的粒子群优化算法的原理,并用改进的带约束的粒子群优化算法优化PSS的参数,将PSS的整个设计过程转化为一组参数进行寻优的过程,提高了多参数寻优的效率。用Matlab仿真软件进行仿真,仿真结果表明,利用该方法设计的PSS,它的小信号稳定性有了较大的提高。     

An efficient technique for real-time control of system voltages and reactive power

This paper presents an efficient technique for the real-time control of reactive power dispatch. The proposed technique is based on a new voltage-reactive power model. This new model linearizes the load flow equations in Cartesian form with proper compensation to the second-order terms. The optimization process is non-iterative and thus is suitable for on-line applications. Different objective functions are incorporated in a global optimization technique and a multi-objective linear programming is formulated to solve this multiple decision-making problem. The non-dominance of the best compromise solution for the multiple objectives is assured by utilizing the operator-computer interactive capabilities of the multi-objective linear programming to reflect the urgency of the operating conditions and/or the predicted situations of the power system operation.     

基于混合粒子群优化算法的PSS参数优化

将一种新的进化算法—粒子群优化算法(PSO)应用到电力系统稳定器(PSS)参数优化当中,文中使用引入交叉操作的混合粒子群优化算法(HPSO),可以获得更好的全局搜索能力和收敛速度。先以低频振荡范围内(0.1~2Hz)PSS产生的附加阻尼转矩ΔTe与Δω尽可能同相位为目标优化PSS超前-滞后环节参数;再以小扰动时发电机功率和角速度振荡最小为目标整定PSS放大倍数。优化结果表明,HPSO算法可以有效地解决PSS参数优化问题。     

基于混合粒子群优化算法的PSS参数优化

将一种新的进化算法-粒子群优化算法(PSO)应用到电力系统稳定器(PSS)参数优化当中,文中使用引入交叉操作的混合粒子群优化算法(HPSO),可以获得更好的全局搜索能力和收敛速度.先以低频振荡范围内(0.1～2 Hz)PSS产生的附加阻尼转矩△Te与△ω尽可能同相位为目标优化PSS超前-滞后环节参数;再以小扰动时发电机功率和角速度振荡最小为目标整定PSS放大倍数.优化结果表明,HPSO算法可以有效地解决PSS参数优化问题.     

An efficient heuristic algorithm for reconfiguration based on branch power flows direction

This paper presents a meshed algorithm for optimal reconfiguration of distribution systems. In the reconfiguration problem, the final objective is to reach a radial network that optimizes some function like the network losses. Many algorithms start from a radial network where a switch closure is complemented by opening of another switch to ensure a radial network. These radial algorithms have an inherent inconvenient, that is, the final solution depends on the initial radial network selected. Other group of algorithms initially represent the distribution network as a meshed network and then open switches until a radial system is obtained. In this paper, to avoid the above aforementioned inconvenient of radial algorithms, a meshed algorithm is used. Furthermore, taking into account that breakpoint nodes are defined as the nodes where the branch power flows converge, the contribution of this paper is to provide a method for solving the problem when multiple loops are considered using an approach based on the breakpoint nodes, since it is complicated to associate each breakpoint node with its corresponding loop. On the other hand, one of the drawbacks of the reconfiguration problem is the need to solve a great number of power flow computations for calculating the losses in each stage of the algorithm. The algorithm proposed has the property that reduces the number of power flows. By this way, the execution time of the algorithm is improved. Besides, it is not necessary to check the network connectivity at each step of the procedure. To prove the effectiveness of the proposed algorithm several test systems have been used, achieving good results.