2021
DOI: 10.1002/2050-7038.12912
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Parameter tuning of PSS and STATCOM controllers using genetic algorithm for improvement of small‐signal and transient stability of power systems with wind power

Abstract: Summary This work demonstrates the impact and robust coordination control among the Doubly Induction Generator (DFIG) and Synchronous Generators (SGs) with Power Oscillation Damping (POD), Power System Stabilizer (PSS),and STATic synchronous COMpensator (STATCOM) on the critical Low‐Frequency Oscillations (LFOs). These modes occurred due to system uncertainty, which leads to power flow interruption and experiences instability. It is mitigated by the proposed location and optimal coordinated optimized gain para… Show more

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Cited by 8 publications
(4 citation statements)
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“…This technique explores genetic mutations and crossover. GA is explored in [145] to enhance oscillation damping by tuning the PSS and STATCOM parameters. However, this optimization approach has some drawbacks, including performance degradation and pre-convergence, especially when used to solve multi-dimensional engineering problems.…”
Section: Genetic Algorithmsmentioning
confidence: 99%
“…This technique explores genetic mutations and crossover. GA is explored in [145] to enhance oscillation damping by tuning the PSS and STATCOM parameters. However, this optimization approach has some drawbacks, including performance degradation and pre-convergence, especially when used to solve multi-dimensional engineering problems.…”
Section: Genetic Algorithmsmentioning
confidence: 99%
“…As a clean and carbon-free renewable energy, wind is one of the most important energy sources on earth. In fact, in addition to lower maintenance and running costs, wind farms need less installation space [5]. However, recent studies have shown that as the penetration levels of wind power plants (WPPs) in power grids increase, problems related to stability and reliability also increase [6,7].…”
Section: Introductionmentioning
confidence: 99%
“…Many scholars have done much research on the parameter optimization of PSS (Abd-Elkareem et al, 2021). Many optimization algorithms have been used to optimize the parameters of PSS, including the well-known genetic algorithm (GA), particle swarm optimization (PSO) algorithm, firefly algorithm (FA), and novel moth-flame optimization (MFO) algorithm in Bhukya and Mahajan (2021), Rodrigues et al (2021), Farhad et al (2018) and Rout and Pati (2018). All these studies have also achieved promising results.…”
Section: Introductionmentioning
confidence: 99%