A Low-Data-Dependence Assessment Method of Industrial Process Interruption Probability Due to Voltage Sag

Abstract

Information about the interruption probability of sensitive industrial processes is important for devising mitigation strategies against voltage sags. However, the existing method for assessing interruption probability is less practical, owing to the difficulty in collecting technical information and data from industrial users. This study proposes a low-data-dependence assessment method for the interruption probability of an industrial process. First, it establishes a general assessment model for the tripping probability of sensitive equipment. Second, it proposes a parameter estimation method to determine the probability density function of the voltage tolerance curve of sensitive equipment in the uncertainty region, according to the equipment trip information recorded by the user. This improves the accuracy of the assessment. Third, this study establishes the logic function expression form of the industrial process structure to describe the relationship between the process interruption probability and the equipment tripping probability. Finally, it proposes a solution method for the process interruption probability based on a heuristic search algorithm, which overcomes the problem of technological process information acquisition, such as the logical relationship among various equipment in the industrial process. The rationality and applicability of the proposed method are verified through a case study.