System Voltage Sag Performance Estimation

A systematic approach for evaluating economic impact of voltage dips

“…From monitoring, almost all the characteristics can be captured and their statistics can be readily obtained. The same data can also be obtained through computer modelling and simulation of the fault events, considering the action of protective relays and the behaviour of generators, motors, and other loads [12]. With sufficient details, all the characteristics and corresponding statistics can also be realised.…”

Grid Voltage Synchronization for Unbalanced Voltages Using the Energy Operator

“…In these applications, grid voltage imbalance may occur caused by asymmetrical transient faults [1][2][3] and this makes it challenging to synchronise the converters to the grid. It is however expected that under such conditions, a chosen synchronization scheme that is able to accurately identify and quickly lock on to the frequency and phase angle changes is used [4][5][6][7].…”

Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

“…Detailed discussion of advantages and disadvantages of these approaches in general and related to specific types of simulation studies is provided in many past papers including [3,4,[15][16][17][18][19]. Similarly, a number of approaches have been proposed to assess single-site indices, including fault positions-based stochastic method [20][21][22][23][24], critical distances [22,23] and Monte Carlo (MC)-based stochastic approaches [15,16,20,25].…”

“…A stochastic assessment of voltage sags is used in [26] to get the expected number and characteristics of sags using deterministic short circuit simulations and the stochastic data of the faults. Furthermore, an analytical method which does not consider the stochastic nature of network parameters and calculates sag duration based on mathematical model is used to produce the voltage sag density table in [4]. Typically, fault position and analytical methods provide long-term mean values of sag performance at a bus, while MC simulation methods allow for uncertainty to be taken into account during the assessment and provide complete distribution function that describes sag performance at the bus.…”

“…Sag severity at certain location can be presented through probability density and distribution functions [3]. Furthermore, the sag information can be compressed into a sag table which groups the sags based on the interval of residual voltage and duration [4][5][6][7][8][9], or by using modified reliability based SAIFI index [10][11][12]. These single-site indices simply give the number of events per year within a certain range of magnitude and duration, resulting in discrete representation of sag characteristics.…”