Indices of Intermittence to Improve the Forecasting of the Voltage Sags Measured in Real Systems

A Method for Real-Time Prediction of the Probability of Voltage Sag Duration Based on Harmonic Footprint

“…After statistical analysis, the sags´ duration and magnitude distributions, and the probability distribution functions were obtained [54][55][56][57]. Recently, such an approach has been used to develop a stochastic model for forecasting voltage sags in a real grid [58][59][60][61]. In [58], the stochastic characterization of voltage sag data obtained from long-term monitoring in a Portuguese grid is presented.…”

“…High accuracy was achieved, i.e., the forecast presented an error slightly greater than 10%. The method was further improved in [61] by introducing special indices of intermittence to detect and remove grouped voltage sags (clusters). In this case, rare voltage sags can be predicted.…”

Measured Rare Voltage Sags and Clusters of Sags: Prediction Models Driven by the Intermittence Indices

“…This feature was first evidenced in [16]. This constitutes a crucial aspect that influences the statistical modeling of measured voltage sags and their practical application in forecasting sags at every site within an entire electrical system, as demonstrated in [17][18][19][20][21]. Rare voltage sags can be modeled effectively as a Poisson process with a constant and positive rate of occurrence owing to their features of timeinvariance, memory-independence, and independence from each other.…”

“…Instead, clusters of sags do not have these characteristics. They typically are dependent events because they are linked to common phenomena that are external to electric systems, such as bad weather conditions, storms, and fires [16,19]. In [17][18][19], the forecast of rare sags was proven to be possible only if the clusters were ascertained and removed.…”

“…They typically are dependent events because they are linked to common phenomena that are external to electric systems, such as bad weather conditions, storms, and fires [16,19]. In [17][18][19], the forecast of rare sags was proven to be possible only if the clusters were ascertained and removed. In [19] new intermittence indices were proposed to improve the removal of the clusters and the successive forecast of rare sags.…”