A Novel Approach of Voltage Sag Data Analysis Stochastically: Study, Representation, and Detection of Region of Vulnerability

Abstract

A voltage sag is a major power quality problem at any load location, mainly due to short circuit faults. Its effects are especially clear in the industrial sector because they lead to direct financial losses. The first and most important step to getting rid of or at least reducing voltage sag is to find the places in the network where it can happen. So, this article discusses a creative way to find the weak spots in a network where the voltage is more likely to drop. This innovative strategy is based on correlation and a stochastic normal probability distribution. The voltage sag is evaluated using an analytical method. The method simulates the number, type, and location of faults randomly throughout the system. After gathering voltage dip data, it is analyzed using normal probability distribution and correlation concepts. The correlation concept provides the relationship between the sag frequency and other parameters, and the sag occurrence area was indicated by the normal probability distribution. After that, the region of vulnerability (ROV) is developed using the ROV flow chart. This paper uses an IEEE 30-bus RTS system as a case study to demonstrate the usefulness of the suggested strategy using MATLAB software.