Power system oscillation damping by intelligent power system stabilizer

Sragdhara Bhattacharya
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引用次数: 7

Abstract

Power Systems are inherently non-linear systems that are frequently subjected to various disturbances causing oscillations at low frequencies that may lead to instability. Generators are usually provided with power system stabilizers minimize the effect of these oscillations. The objective of this paper is find the optimal parameters for a conventional “lead-lag compensator based Power System Stabilizer (PSS)” for a system comprising of a “generator connected to an infinite bus” and containing a ST1A type excitation system. The tuning of the parameters of the “Power System Stabilizer” is accomplished using the “Particle Swarm Optimization (PSO)” algorithm. In this paper, a Fuzzy Power System Stabilizer (FPSS) where the optimal values of the parameters of the FPSS are decided using the PSO algorithm is also designed. The Particle Swarm Optimization based conventional PSS and the “Particle Swarm Optimization based Fuzzy PSS” are also incorporated in a system containing multiple machines to check the system responses under different loading conditions and faults of different types. The simulation results clearly prove the efficiency of the PSO based conventional and fuzzy power system stabilizers in damping the low frequency speed and power oscillations occurring in the power system due to various disturbances.
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智能电力系统稳定器对电力系统振荡的抑制
电力系统本质上是非线性系统,经常受到各种干扰,导致低频振荡,可能导致不稳定。发电机通常配备电力系统稳定器,以尽量减少这些振荡的影响。本文的目标是为一个由“连接到无限母线的发电机”和包含ST1A型励磁系统组成的系统找到传统的“基于超前滞后补偿器的电力系统稳定器(PSS)”的最佳参数。采用“粒子群优化”算法对“电力系统稳定器”参数进行整定。本文还设计了一种模糊电力系统稳定器(FPSS),利用粒子群算法确定其参数的最优值。并将基于粒子群优化的传统PSS和基于粒子群优化的模糊PSS结合到多机系统中,对不同负载条件和不同类型故障下的系统响应进行了检验。仿真结果清楚地证明了基于粒子群的传统和模糊电力系统稳定器在抑制各种干扰引起的电力系统低频调速和功率振荡方面的有效性。
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