This paper studies the impact of leveraging both static synchronous compensator (STATCOM) and power system stabilizer (PSS) on multi-machine power systems. Considering a standard IEEE 9-bus test power network, classic and intelligent controllers are applied to achieve the desirable system performance. Simulated tests show the usefulness of STATCOM on network power quality in terms of voltage profile. In addition, it is shown that it can significantly improve the damping oscillations of synchronous generator under normal and abnormal network conditions. As shown, the PSS also contributes to improving the synchronous generator parameters. It is also observed that using intelligent controllers with STATCOM and PSS leads to a better performance relative to the classic controllers.
In this paper, a small-signal dynamic model of a single-machine infinite-bus (SMIB) power system that includes IEEE type-ST1 excitation system and PSS based on transfer function structure is presented. The changes in the operating condition of a power system on dynamic performance have been examined. The dynamic performance of the closed-loop system is analyzed base on its eigenvalues. The effectiveness of the parameters changes on dynamic stability is verified by simulation results. Three types of PSS have been considered for analysis: (a) the derivative PSS, (b) the lead-lag PSS or conventional PSS, and (c) the proportional-integral-derivative PSS. The objective function is formulated to increase the damping ratio of the electromechanical mode eigenvalues. Simulation results show that the PID-PSS performs better for less overshoot and less settling time compared with the CPSS and DPSS under different load operation and the significant system parameter variation conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.