scholarly journals WAMS based Thevenin Index for voltage stability assessment with increasing wind power penetration and additional distributed load

2022 ◽  
Vol 8 ◽  
pp. 672-683
Author(s):  
Raju Chintakindi ◽  
Pradyumna Pradhan ◽  
Arghya Mitra
2020 ◽  
Author(s):  
Moumita Sarkar ◽  
Anca Daniela Hansen ◽  
Poul Ejnar Sørensen

Traditional voltage stability assessment methods do not include temporal variation of renewable power generations like wind. This paper proposes a novel methodology for probabilistic voltage stability assessment methodology which can be used in conjunction with any of the existing traditional voltage stability indices. Historical wind power data are used to determine probabilistic distribution of wind power at future instant based on wind power value at current instant. Based on the probabilistic risk of increase and decrease of wind power at future instant, two probabilistic voltage stability indices are computed. The worse case value among the two indices are used as prediction of voltage stability index at future instant, based on current system parameters. Effectiveness of the proposed methodology in predicting proximity of the system voltage collapse is illustrated through case studies and time-series simulations. Results show that proposed methodology predicts more realistic proximity to voltage collapse than traditional stability assessments.<br>


2020 ◽  
Author(s):  
Moumita Sarkar ◽  
Anca Daniela Hansen ◽  
Poul Ejnar Sørensen

Traditional voltage stability assessment methods do not include temporal variation of renewable power generations like wind. This paper proposes a novel methodology for probabilistic voltage stability assessment methodology which can be used in conjunction with any of the existing traditional voltage stability indices. Historical wind power data are used to determine probabilistic distribution of wind power at future instant based on wind power value at current instant. Based on the probabilistic risk of increase and decrease of wind power at future instant, two probabilistic voltage stability indices are computed. The worse case value among the two indices are used as prediction of voltage stability index at future instant, based on current system parameters. Effectiveness of the proposed methodology in predicting proximity of the system voltage collapse is illustrated through case studies and time-series simulations. Results show that proposed methodology predicts more realistic proximity to voltage collapse than traditional stability assessments.<br>


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