Predicting the Number of Voltage Sags Using the SARFI Index Considering System Uncertainties

These days, a wide range of sensitive loads and distributed energy resources are being utilized in the electrical network. Premised on the nature of these loads, when a voltage sag occurs, the sensitive loads may be severed from the network, or their normal operation may be disrupted. Furthermore, it can lead up to enormous financial losses. Hence, it is crucial to estimate the quantity of voltage sags which can impact the sensitive load. The operation of protection systems and load levels, as well as uncertainties of distributed energy resources play a major role in evaluating power quality, especially in the voltage sag phenomenon. In the current paper, a probabilistic method is put forth for estimating the frequency of voltage sag using the system average root-mean-square variation frequency (SARFI) index in light of system uncertainties, inter alia, distributed energy resources and sensitive loads, as well as malfunctions of the protection system. The proposed method is employed on the IEEE-30 test system. The results of utilizing the proposed method illustrate that the quantity of voltage sags is related to pre-fault voltage, which is correlated with load levels and distributed energy resources. Also, if the primary protection system cannot operate and the backup protection system cleans the fault, the number of voltage sags increases.