A simplified stability analysis method for LV inverter-based microgrids

Dağ, Bülent; Aydemir, M. Timur

doi:10.1007/s40565-018-0478-1

Cited by 6 publications

(2 citation statements)

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“…The islanded mode of the distributed generators (DG's) operation helps with rural electrification because of its autonomous operation. The connection between the primary grid and the DGs operates in a stiff grid mode, wherein voltage and frequency measurements derived from the primary grid assume the phase-locked loop (PLL)-based synchronization, a concept in the study by Dağ and Aydemir [1]. Analyzing the stability of an islanded microgrid is a complex process that requires the examination of steady-state variables and performing eigen analysis on those variables [1].…”

Section: Introductionmentioning

confidence: 99%

“…The connection between the primary grid and the DGs operates in a stiff grid mode, wherein voltage and frequency measurements derived from the primary grid assume the phase-locked loop (PLL)-based synchronization, a concept in the study by Dağ and Aydemir [1]. Analyzing the stability of an islanded microgrid is a complex process that requires the examination of steady-state variables and performing eigen analysis on those variables [1]. The stability assessment of an islanded microgrid involves studying the behavior of steady-state variables and performing eigen analysis to determine its stability.…”

Section: Introductionmentioning

confidence: 99%

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Steady state stability assessment of voltage source converter in a DC microgrid under weak grid conditions

Viswanathan,

Jayaramaiah

2024

IJPEDS

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Traditionally, steady-state assessment involves analyzing numerous variables using Eigen analysis. This paper presents a decision support application for diagnosing the steady-state assessment of droop-controlled voltage source inverters in islanded microgrid operations or weak grid operations with reduced input attributes. This paper proposes an approach using feature extraction from the state space variables of the droop-controlled voltage source inverter (VSI). Photovoltaic (PV) and wind energy sources are considered with their stipulated power-delivering capability considered. To improve the generalization of the predictive model, preprocessing techniques are employed to eliminate data distortions. Dimensionality reduction is achieved through principal component analysis (PCA) applied to the steady-state variables. The evaluation of the VSI's steady-state stability is conducted utilizing support vector classification algorithm. To ascertain the reliability of the steady-state stability classification, an assessment of the support vector machine (SVM) model's performance is carried out, which includes the examination of metrics like the area under the curve (AUC) and the receiver operating characteristics (ROC) curve. The findings from the assessment of VSI's steady-state stability indicate a commendable level of performance, achieving an accuracy rate of 93.5%.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%