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首页> 外文期刊>IEEJ Transactions on Electrical and Electronic Engineering >STATCOM versus SSSC for power system stabilization
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STATCOM versus SSSC for power system stabilization

机译:STATCOM与SSSC用于电源系统稳定

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Flexible alternating current transmission systems (FACTS) are gaining more attention in power utilities because of their advantages of controllability, reliability, and operation over a wide range. Static synchronous compensator (STATCOM) and static series synchronous compensator (SSSC) are prominent FACTS topologies; they have the ability to instantaneously regulate active/reactive powers and stabilize the power system following severe disturbances. In this paper, STATCOM and SSSC are compared with regard to their damping action on power system oscillations. The comparison is extended to the controller design strategies. Two distinct meta-heuristic optimization approaches, namely chaos (CO) and simulated annealing (SA), are recommended for the optimal design of the SSSC and STATCOM damping controller. To assess the promising FACTS topology, a single-machine infinite bus system is subjected to several disturbances while operating at different loading levels. MATLAB/Simulink is used as a platform to investigate the dynamic performance of the system under consideration with STATCOM and SSSC. Simulation results reveal the superiority of SSSC in damping power system oscillations in terms of response speed and stability margin. Moreover, the CO optimization scheme seems to outperform the SA algorithm in terms of computation requirements and global optimal convergence. (c) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
机译:灵活的交替交流传输系统(事实)由于其可控性,可靠性和运行优势在广泛范围内而引起了电力公用事业的更多关注。静态同步补偿器(STATCOM)和静态系列同步补偿器(SSSC)是突出的事实拓扑。他们有能力在严重干扰后立即调节主动/反应能力并稳定电力系统。在本文中,将STATCOM和SSSC在其对电源系统振荡的阻尼作用方面进行了比较。比较扩展到控制器设计策略。建议采用两种不同的元元素优化方法,即混乱(CO)和模拟退火(SA),以用于SSSC和STATCOM阻尼控制器的最佳设计。为了评估有希望的事实拓扑,在以不同的负载水平运行时,单机无限总线系统受到了几次干扰。 MATLAB/SIMULINK用作使用STATCOM和SSSC考虑系统的动态性能的平台。仿真结果揭示了在响应速度和稳定性边缘方面,SSSC在阻尼电源系统振荡中的优势。此外,在计算要求和全局最佳收敛方面,CO优化方案似乎优于SA算法。 (c)2017年日本电气工程师研究所。由John Wiley&Sons,Inc。出版

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