Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

2020 ◽  
Author(s):  
Moumita Sarkar ◽  
Anca Daniela Hansen ◽  
Poul Ejnar Sørensen
Keyword(s):  
Wind Power ◽  
Voltage Stability ◽  
Current System ◽  
Stability Index ◽  
Voltage Collapse ◽  
Assessment Methodology ◽  
Stability Assessment ◽  
Renewable Power ◽  
Probabilistic Distribution ◽  
Stability Indices

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>

scholarly journals Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

2020 ◽  
Author(s):  
Moumita Sarkar ◽  
Anca Daniela Hansen ◽  
Poul Ejnar Sørensen
Keyword(s):  
Wind Power ◽  
Voltage Stability ◽  
Current System ◽  
Stability Index ◽  
Voltage Collapse ◽  
Assessment Methodology ◽  
Stability Assessment ◽  
Renewable Power ◽  
Probabilistic Distribution ◽  
Stability Indices

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>

scholarly journals Voltage Collapse Prediction of IEEE 30-Bus system

2021 ◽  
Vol 28 (1) ◽  
pp. 98-112
Author(s):  
Mohammed Ibrahim ◽  
Abdulsattar Jasim
Keyword(s):  
Power System ◽  
Modal Analysis ◽  
Voltage Stability ◽  
Stability Index ◽  
Maximum Load ◽  
Voltage Collapse ◽  
Analysis Method ◽  
The Stability ◽  
Stability Indices ◽  
Participation Factor

Voltage collapse in the power system occurs as a result of voltage instability, thus which lead to a blackout, and this is a constant concern for network workers and customers alike. In this paper, voltage collapse is studied using two approved methods: the modal analysis method and voltage stability indices. In the modal analysis method, the eigenvalues were calculated for all the load buses, through which it is possible to know the stability of the power system, The participation factor was also calculated for the load buses, which enables us to know the weakest buses in the system. As for the Voltage stability Indices method, two important indices were calculated, which are: Fast Voltage Stability Index (FVSI) and Line stability index (Lmn). These two indices give a good visualization of the stability of the system and the knowledge of the weakest buses, as well as the Maximum load-ability of the load buses. The above mentioned two methods were applied using software code using MATLAB \ R2018a program to the IEEE 30-Bus test system. In the modal analysis, the buses which have the maximum participation factor are 26, 29, and 30 this indicates that they are the weakest in the system. as well as in the voltage stability indices. These buses have the lowest maximum load ability which demonstrates the possibility of using both methods or one of them to study the voltage collapse.

scholarly journals A Research on Selection of Appropriate Stability Index under Adverse System Conditions for the Assessment of Voltage Stability of an IEEE 14 Bus Power System

2020 ◽  
Vol 22 (6) ◽  
pp. 435-446
Author(s):  
Pawan Kumar Kushwaha ◽  
Chayan Bhattacharjee
Keyword(s):  
Voltage Stability ◽  
Reactive Power ◽  
Stability Index ◽  
Performance Comparison ◽  
Operating Conditions ◽  
Voltage Collapse ◽  
Stability Assessment ◽  
Contingency Ranking ◽  
Generation Unit ◽  
Selection Of

For voltage stability assessment at a given operating point, various types of voltage stability indices (VSIs) have been proposed in the literature. In this paper, the voltage stability assessment of an IEEE-14 bus system is done for performance comparison of different types of VSIs available, under certain critical and practical stressed operating conditions (SOCs). The performance comparison of various VSIs under the considered SOCs is not reported in the literature. Such SOCs include the combinational occurrence of – variation in inductive loading, single line to ground (SLG) fault and effect of one generation unit tripped. These SOCs are the prime cause of voltage collapse of any node/line. The results show the performance of various VSIs with respect to line number, contingency ranking of the line, power margin, effects of loading and SLG fault. These VSIs are also instrumental in critical line and node analysis (CLNA) which is useful in the choice of proper location for reactive power compensation required. The simulated results provide the best performing VSI for accurate prediction of voltage instability under any considered SOC. This information is essential for voltage stability assessment of a particular line under multiple causes of voltage collapse.

scholarly journals Implementation of Static Line Voltage Stability Indices for Improved Static Voltage Stability Margin

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Natakorn Thasnas ◽  
Apirat Siritaratiwat
Keyword(s):  
Optimal Power Flow ◽  
Voltage Stability ◽  
Stability Margin ◽  
Stability Index ◽  
System Stability ◽  
Line Voltage ◽  
Voltage Stability Index ◽  
Static Voltage Stability ◽  
Voltage Stability Margin ◽  
Stability Indices

Nowadays, the changes of economic, environment, and regulations are forcing the electric utilities to operate systems at maximum capacity. Therefore, the operation and control of power system to improve the system stability has been receiving a great deal of attention. This paper presents an approach for enhancing the static voltage stability margin and reducing the power losses of the system with voltage security-constrained optimal power flow (VSC-OPF) that is based on static line voltage stability indices. The control approaches incorporate the voltage stability criteria into the conventional OPF. The minimization of the summation of fast voltage stability index (FVSI), line stability index (Lmn), and line voltage stability index (LVSI) is used as the objective functions. The performance and effectiveness of the proposed control approaches are evaluated on the standard IEEE 30-bus, 57-bus, and 118-bus test systems under normal and contingency conditions. The comparison analysis is carried out with different cases including minimization of generation cost. The proposed control approaches indicate the promising results and offer efficient countermeasures against the voltage instability of the system.

Sign in / Sign up

Export Citation Format

Share Document