Voltage Sags: Validating Short-Term Monitoring by Using Long-Term Stochastic Simulation

This paper presents a procedure to validate voltage sag results based on a short-term monitoring program and stochastic assessment of voltage sag characteristics. The main practical use of this methodology is to analyze the accuracy of sag characteristics obtained from short monitoring periods. With a Monte Carlo Simulation approach, probabilistic models of several factors are taken into account: lines and busbars fault rate, prefault voltage, fault-type distribution, fault-location uncertainty, and fault resistance distribution. Confidence intervals based on the percentile method and hypothesis tests are the statistical tools selected to perform the validation of voltage sags magnitude and frequency. A case study based on the evaluation of a six-month monitoring period shows the applicability of the proposed methodology.