Implementation of Particle Swarm Optimization (PSO) Algorithm for Tuning of Power System Stabilizers in Multimachine Electric Power Systems
Citations Over TimeTop 10% of 2020 papers
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.
Related Papers
- → Parameter meta-optimization of metaheuristics of solving specific NP-hard facility location problem(2018)26 cited
- → A bibliography of metaheuristics-review from 2009 to 2015(2018)22 cited
- → Adaptive and Multilevel Metaheuristics(2018)9 cited
- → Adaptive and Multilevel Metaheuristics(2018)7 cited
- → Mathematical model automotive part shape optimization using metaheuristic method-review(2021)2 cited