A novel approach for voltage sag representation in a chemical industry: A case study. Issue 7 (15th June 2020)

• Record Type: Journal Article
• Authors: Behera, Chinmaya; Banik, Abhishek; Goswami, Arup Kumar
• Is Part Of: Engineering reports. Volume 2:Issue 7(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-15
• Subjects: impedance modeling -- industrial distribution system -- MCS -- Monte Carlo simulation -- power quality -- sag map -- symmetrical and unsymmetrical faults -- voltage sag; Engineering -- Periodicals; Computer science -- Periodicals; 620.005
• DOI: 10.1002/eng2.12198
• Languages: English
• ISSNs: 2577-8196

Abstract

Abstract: Voltage sag is a major Power Quality issue which may occur at every possible load point. In the industrial sector, its impact is particularly prominent at it is directly related to financial losses. To eliminate or, at least, mitigate voltage sag, the first, and the most crucial, step is to identify the portions of the network which are vulnerable to voltage sag. Therefore, a novel approach is presented in this article to identify the areas within the network, which are more prone to voltage sag. An impedance matrix‐based model followed by Monte Carlo Simulation (MCS) technique is used for the assessment of the voltage sag. This MCS technique is implemented to simulate the number, type, and locations of faults randomly within the system. Then, voltage sag data are collected, and using Bivariate Frequency Distribution, a graphical representation of voltage sag prone buses is developed, which named Voltage Sag Map. The effectiveness of the proposed approach is validated by adopting an industrial distribution system as a case study in this article. Abstract : Voltage sag is a major Power Quality (PQ) issue which may occur at every possible load point. In the industrial sector, its impact is particularly prominent as it is directly related to financial losses. In order to eliminate or, at least, mitigate voltage sag, the first, and the most crucial, step is to identify the portions of the network which are vulnerable to voltage sag. To address this issue, a novel approach is presented in this article to identify the areas within the network which are more prone to voltage sag.