Abstract
The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.
Highlights
Electric power systems (EPS) are continuously evolving towards more complex systems considering the incorporation of non-conventional renewable energies (NCRE), flexible AC transmission systems (FACTS) and distributed generation
There are a number of articles referring to the tuning of power stabilizers, where different tools are used as fitting methodology
This study aims at implementing the Particle Swarm Optimization (PSO) algorithm using the programming language of DigSilent
Summary
Electric power systems (EPS) are continuously evolving towards more complex systems considering the incorporation of non-conventional renewable energies (NCRE), flexible AC transmission systems (FACTS) and distributed generation. It is necessary to have appropriate control devices that allow to ensure a better dynamic response. In this context, one current and future challenge is the tuning of controller parameters that guarantee the best response of the system to perturbations and events that might represent a risk for the stability of the electric system. There are a number of articles referring to the tuning of power stabilizers, where different tools are used as fitting methodology. In reference [1], a tuning of the PSS gain is carried out, using the root locus method. In [2], an optimal power system stabilizer (OPSS)
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