Static Voltage Stability Assessment Considering Impacts of Ambient Conditions on Overhead Transmission Lines

Jia, Xueyong; Dong, Xiaoming; Xu, Bing; Qi, Fujun; Liu, Zhengqi; Ma, Yue; Wang, Yan

doi:10.1109/tia.2022.3195974

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…In [39] Machine Learning (ML) is utilized to forecast the loadability margin, which functions as a surrogate for the margin of sustained voltage stability. The [40] article suggests a single power flow model that takes into account the electrothermal coupling effect, which is represented by the equilibrium between heat dissipation and absorption for conductors above ground. The Critical Voltage-Reactive Power Ratio (CVQR) index is a QVbased technique that is described in [41] to assess the voltage instability tendencies of power system buses with increasing penetration of renewable energy (RE).…”

Section: Introductionmentioning

confidence: 99%

Voltage stability assessment of the power system using novel line voltage collapse index

Gupta,

Mallik,

Kumar

et al. 2024

Eng. Res. Express

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Nowadays, for the maximum utilization of the power available, power systems are operated at their maximum stability limit due to the scarcity of natural resources. In this situation, quick monitoring and control of the power systems are very necessary for the electrical operators. This paper presents a novel line voltage stability index based on V-Q sensitivity. The index is created utilizing the network’s ABCD parameters and is based on an exact transmission system model. The new index is evaluated in terms of ABCD parameters from the reactive power equation of the power system. The proposed line index can predict the voltage collapse under heavy MVA loading, heavy reactive loading, randomly chosen heavy reactive loading, and different N-1 contingencies conditions. This has also the capability to predict voltage stability under different contingencies. The proposed method is compared with four existing methods named line stability index (Lmn), fast voltage stability index (FVSI), line stability factor (Lqp), and line voltage stability index (LVSI). Results show that the critical situation of the power system that has been investigated by the proposed approach is more accurate than these four existing methods under different operating scenarios. The accuracy and applicability of the proposed method are investigated on IEEE 14-bus and IEEE 118-bus systems.

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Section: Introductionmentioning

confidence: 99%

Voltage stability assessment of the power system using novel line voltage collapse index

Gupta,

Mallik,

Kumar

et al. 2024

Eng. Res. Express

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show abstract

“…Voltage stability can be rapidly assessed using a variety of stability metrics [13].. The unified power flow model described in [14] provides support for the electrothermal coupling effect, which is characterized by the balance of heat absorption and dissipation for overhead conductors. Additionally, the power flow calculation takes into account the geographic and meteorological data near the transmission lines as variables.…”

Section: Introductionmentioning

confidence: 99%

Fast assessment of the voltage stability using reconfigured power system network and artificial neural network approaches

Gupta,

Mallik

2023

Eng. Res. Express

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Planning and running power systems must take voltage stability into account. Instability is mostly caused by the power system's failure to supply the demand for reactive power. The voltage stability margin must be understood by utilities if they are to operate the power system with the highest level of security and dependability. This paper uses reconfigured 12 bus, 10 bus, and 8-bus reconfigured networks of the interconnected IEEE 14 bus system to demonstrate the proposed quick method for assessing the voltage stability. The original (IEEE 14 bus) and the reconfigured (12 bus, 10 bus, and 8-bus) systems' voltage stability has been evaluated using the line stability index indicators: fast voltage stability index (FVSI), line voltage stability index (LVSI), and line stability index (Lmn). Based on the maximum loadability factor, the contingencies for the original and reconfigured systems are ranked. The system loadability factor is used as the input parameter, and the LVSI, Lmn, and FVSI indices for the critical line under critical contingency are used as an output to train the ANN network. It has been found that there is no discernible difference between the actual (NR method) and predicted (ANN approach) output. For accessing the voltage stability of the IEEE 14 bus system by its reconfigured networks using the proposed approach, the computational time and error are very low, showing the effectiveness, rapidity, and accuracy of the suggested approach.

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Interval Prediction of Dynamic Line Rating of OHL Based on Improved Affine Arithmetic

Li,

Liu,

et al. 2024

Lecture Notes in Electrical Engineering

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Static Voltage Stability Assessment Considering Impacts of Ambient Conditions on Overhead Transmission Lines

Cited by 4 publications

References 22 publications

Voltage stability assessment of the power system using novel line voltage collapse index

Voltage stability assessment of the power system using novel line voltage collapse index

Fast assessment of the voltage stability using reconfigured power system network and artificial neural network approaches

Interval Prediction of Dynamic Line Rating of OHL Based on Improved Affine Arithmetic

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