Estimation of time to voltage collapse

A comprehensive assessment to propose an improved line stability index

“…According to the results of this analysis shown in Table 10, the outage of lines 16-19 and 01-02 results in the lowest loading margin, 89 and they are the most severe contingencies. In this regard, the outage of lines 01-02 and [16][17][18][19], which occur at t = 5 s and t = 25 s, respectively, will be simulated.…”

“…It should be noted that in deriving these indicators, active power ( P ) and reactive power ( Q ) are assumed to flow from the sending bus (SB) to the receiving bus (RB). Bus voltage stability indices: These indices are used to detect the distance between existing operating point and the maximum loading (ML) of load busses, which results in identification of weakest bus in the system. It is worth mentioning that the implementation of these indices is more complicated and they have more computational burden than line stability indices. Other indices: In addition to line and bus stability indices, there are some other methods like modal analysis, sensitivity analysis, artificial intelligence tools, on‐load tap‐changer (OLTC)–based methods, P‐Q and P‐V curve‐based methods, minimum singular value (MSV) of the power‐flow Jacobian, MSV of the reduced Jacobian, equivalent node voltage collapse index, and energy functions, which can be used to assess the stability of the whole power system. The main drawback of these indices is that they have high computational burden. Obviously, among above‐mentioned tools, the one that can provide more accurate assessment and has lower computational burden will be more effective for online applications.…”

“…It is worth mentioning that the implementation of these indices is more complicated and they have more computational burden than line stability indices. • Other indices: In addition to line and bus stability indices, there are some other methods like modal analysis, 11 sensitivity analysis, 12,13 artificial intelligence tools, 14,15 on-load tap-changer (OLTC)-based methods, [16][17][18] P-Q and P-V curve-based methods, 19 minimum singular value (MSV) of the power-flow Jacobian, 20 MSV of the reduced Jacobian, 21 equivalent node voltage collapse index, 22 and energy functions, 23 which can be used to assess the stability of the whole power system. The main drawback of these indices is that they have high computational burden.…”

Adaptive boundary determination for network reduction in long‐term voltage stability analyses

“…Similar to [26], performance of this time indicator is limited to load disturbances. In [28], estimation of the remained time to voltage collapse has been determined based on virtual acceleration of OLTCs as the main key factor in voltage instability scenarios. In this method, though the time of instability occurrence has been intentionally reduced by decreasing the OLTCs operation time, however, the calculation time of accelerated network is not different from the real network due to iterative process of stopping in the time, doing simple and low-cost computation operations; moreover, returning to the time domain.…”

Estimation of voltage instability inception time by employing k‐nearest neighbour learning algorithm

“…Similar to [24], the performance of this time indicator is limited to load disturbances. In [26], estimation of the remaining time to voltage collapse has been determined based on virtual acceleration of on‐load tap changer (OLTC) of transformers as the main key factor in voltage instability scenarios. In this method, the instability time has been (intentionally) reduced by decreasing the activation time of OLTCs.…”