2016
DOI: 10.9734/psij/2016/24425
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Stability Analysis of the Micro-Grid Operation in Micro-Grid Mode Based on Particle Swarm Optimization (PSO) Including Model Information

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Cited by 6 publications
(4 citation statements)
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“…Zhou et al [35] integrated multi-output SVM (MSVM) and multi-task learning (MTL) for traffic DP in Taipei, Taiwan. Chouikhi et al [36] leveraged a PSO algorithm based on an effective learning process [37] to tune an echo state network (ESN) for time series prediction. Amasyali et al [31] employed ML algorithms such as SVM and ANN for energy consumption DP within several types of buildings.…”
Section: Methods For Dpmentioning
confidence: 99%
“…Zhou et al [35] integrated multi-output SVM (MSVM) and multi-task learning (MTL) for traffic DP in Taipei, Taiwan. Chouikhi et al [36] leveraged a PSO algorithm based on an effective learning process [37] to tune an echo state network (ESN) for time series prediction. Amasyali et al [31] employed ML algorithms such as SVM and ANN for energy consumption DP within several types of buildings.…”
Section: Methods For Dpmentioning
confidence: 99%
“…A substantial amount of work has been undertaken in the recent past to enhance the power quality and control of MGs using PSO. Moghimi et al [16] explored PSO for regulating the voltage and frequency of the DG units in an islanded MG. The power controller parameters (Kp and Ki) were optimized by using the mentioned algorithm in order to obtain the optimal values of the controlled variables for regulating voltage, frequency, active power and reactive power of the studied MG system.…”
Section: Particle Swarm Optimization For Dynamic Response and Powmentioning
confidence: 99%
“…In addition, these intelligent search techniques offer a better solution than conventional mathematical approaches for solving an optimization problem [25]. Several studies have explored different AI techniques such as Fuzzy Logic (FL) [26], the Genetic Algorithm (GA) [25,27], and PSO [3,28] by averting lengthy and inefficient traditional PI tuning methods for MG voltage and frequency control. The optimal values of PI parameters selected by the AI-based optimization algorithms have resulted in a better dynamic response of studied islanded MG systems as compared to the traditional tuning methods.…”
Section: Related Work In Literaturementioning
confidence: 99%