1. Mitigation of SSR and LFO with a TCSC based-conventional damping controller optimized by the PSO algorithm and a fuzzy logic controller
- Author
-
Hasan Ghahramani, Hossein Hosseini, Akbar Lak, and Murtaza Farsadi
- Subjects
Engineering ,General Computer Science ,business.industry ,Particle swarm optimization ,Transmission system ,Subsynchronous resonance,low-frequency oscillation,thyristor-controlled series capacitor,particle swarm optimization,fuzzy logic controller ,Fuzzy logic ,law.invention ,Capacitor ,Electric power system ,law ,Control theory ,Electronic engineering ,Electrical and Electronic Engineering ,Low-frequency oscillation ,business ,MATLAB ,computer ,computer.programming_language - Abstract
The subsynchronous resonance (SSR) phenomenon may occur when a steam turbine-generator is connected to a long transmission line with series compensation. Flexible AC transmission systems (FACTS) devices are widely applied to damp the SSR and low-frequency oscillation (LFO). A thyristor-controlled series capacitor (TCSC) is a commercially available FACTS device that was developed for damping the SSR and LFO. In this paper, 2 control methods for damping the SSR and LFO are added to the TCSC main controller in order to demonstrate that the SSR damping capability of the TCSC can be enhanced by proper modulation of the firing angle. The control methods are presented, namely the conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). The particle swarm optimization (PSO) algorithm is used for searching optimized parameters of the CDC. Fast Fourier transform is carried out in order to evaluate the effect of the TCSC-based FLDC in damping the SSR and LFO. The study system was adopted from the IEEE second benchmark model by altering a part of the fixed series capacitor to the TCSC. The MATLAB/Simulink was used to verify the effectiveness of each control method. The simulation results show that the FLDC has an excellent ability in damping the SSR and LFO in the power system toward the CDC-optimized PSO algorithm.
- Published
- 2014