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

Author

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  • Jagannath Patra

    (Department of Electrical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India)

  • Nitai Pal

    (Department of Electrical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India)

  • Harish Chandra Mohanta

    (Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Bhubaneswar, Odisha 752050, India)

  • Reynah Akwafo

    (Department of Electrical and Electronics Engineering, Bolgatanga Technical University, Sumburungu, Bolgatanga PO Box 767, Ghana)

  • Heba G. Mohamed

    (Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

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.

Suggested Citation

  • Jagannath Patra & Nitai Pal & Harish Chandra Mohanta & Reynah Akwafo & Heba G. Mohamed, 2023. "A Novel Approach of Voltage Sag Data Analysis Stochastically: Study, Representation, and Detection of Region of Vulnerability," Sustainability, MDPI, vol. 15(5), pages 1-29, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4345-:d:1083949
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    References listed on IDEAS

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    1. Jagannath Patra & Nitai Pal, 2022. "A Mathematical Approach of Voltage Sag Analysis Incorporating Bivariate Probability Distribution in a Meshed System," Energies, MDPI, vol. 15(20), pages 1-19, October.
    2. Abdul Hameed Soomro & Abdul Sattar Larik & Mukhtiar Ahmed Mahar & Anwar Ali Sahito, 2022. "Simulation-Based Comparison of PID with Sliding Mode Controller for Matrix-Converter-Based Dynamic Voltage Restorer under Variation of System Parameters to Alleviate the Voltage Sag in Distribution Sy," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    3. Amir Safdarian & Mahmud Fotuhi-Firuzabad & Matti Lehtonen, 2019. "A General Framework for Voltage Sag Performance Analysis of Distribution Networks," Energies, MDPI, vol. 12(14), pages 1-15, July.
    4. Sinan Küfeoğlu & Matti Lehtonen, 2016. "Macroeconomic Assessment of Voltage Sags," Sustainability, MDPI, vol. 8(12), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

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