Online Identification of Tripped Line for Transient Stability Assessment

Abstract

Identification of post-fault topology is critical to not only cascaded outage prevention but also prediction of post-fault dynamic behavior. Existing methods for identifying the tripped lines rely on steady state SCADA/PMU measurements, and therefore fail to accomplish their task within fractions of a second. This limits their application to online transient stability assessment. This paper presents a method for online identification of post-fault topology on the basis of information of the pre-fault operating conditions and synchronized measurements at all generator buses. The proposed technique identifies the tripped line with negligible delay, before the system reaches steady state. An innovative index, which represents the normalized kinetic energy gained by generators immediately after the fault, is used to minimize the search set of possible tripped lines. For every candidate line, the generator output powers are calculated considering the line as tripped, and the minimum error between the measured and the calculated generator powers is used to finally identify the tripped line. The IEEE 39-bus system and a 246-bus North Indian Grid representation are used to show the effectiveness of the method.

Online detection of tripped transmission line to improve wide‐area SA in power transmission system

“…The performance of the proposed scheme is compared with three of the recently proposed schemes [17,21,27]. The following conclusions are inferred though the comparative analysis:…”

“…In recent times, PMU informations are used in applications such as WA protection, state estimation (SE), dynamic security assessment [5][6][7][8][9][10] etc. PMUs are also used to identify the tripped transmission lines [11][12][13][14][15][16][17][18][19][20][21]. Voltage phasor angle measurement-based single line and double line outage detection techniques are reported in [11,12], respectively.…”

“…Li et al of [20] have investigated the impact of PMU with bad data on the line outage detection technique. Recently, a normalised kinetic energy-based scheme is reported in [21]. Most of the recently proposed schemes require higher number of PMUs to be installed in the existing power system.…”

FLiER: Practical Topology Update Detection Using Sparse PMUs

“…According to the IEEE specification, data from a correctly functioning PMU also satisfy tight phase and magnitude error tolerances [20]. Hence, many methods combine PMU data, SCADA data, and model information for state estimation [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33] and for detection and localization of faults [34], [35], [36], [37], [38], [14], [39], [15], [40], [41], [42], [43].…”

Analytical on‐line method of determining transient stability margin using protection information for asymmetric faults

“…The transient stability of power systems is affected by many factors such as fault location, fault type and network structure [7], which could be obtained from the protection information. In some research, the fault locations and fault clearing time are modelled as probabilistic models and the probabilistic transient stability is calculated by Monte Carlo methods [8–10].…”