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Enhancing Resiliency in Distribution Power Grids with Distributed Generation Through Application of Visualisation Techniques

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  • Yasmin Nigar Abdul Rasheed

    (The Australian Power and Energy Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
    School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Ashish P. Agalgaonkar

    (The Australian Power and Energy Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
    School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Kashem Muttaqi

    (The Australian Power and Energy Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
    School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

Abstract

With recent technological advancements, advanced communication technology, sensors and distributed generation (DG), it is an undeniable fact that modern power systems are flooded with massive amounts of data. These vast amount of generated data are difficult to interpret and comprehend, and are slow to sort through and explain. With ever increasing renewable power generation, grid operators should gain insights on identifying the vulnerabilities, behaviour and interactions of various power system components and anticipate challenges to enhance power system resiliency. Visualisation offers a means to reveal patterns, trends and connections in data that speed up and present information to a power system operator in a way that can be well understood topographically and provide an ability to accommodate increasing DG resources. Hence, this paper presents a comprehensive literature review of several visualisation techniques that can be embedded for improving operational efficiency and resiliency in modern power grids embedded with distributed and renewable energy resources.

Suggested Citation

  • Yasmin Nigar Abdul Rasheed & Ashish P. Agalgaonkar & Kashem Muttaqi, 2025. "Enhancing Resiliency in Distribution Power Grids with Distributed Generation Through Application of Visualisation Techniques," Energies, MDPI, vol. 18(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1847-:d:1628978
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    References listed on IDEAS

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    1. Vinoth Kumar Ponnusamy & Padmanathan Kasinathan & Rajvikram Madurai Elavarasan & Vinoth Ramanathan & Ranjith Kumar Anandan & Umashankar Subramaniam & Aritra Ghosh & Eklas Hossain, 2021. "A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid," Sustainability, MDPI, vol. 13(23), pages 1-35, December.
    2. A. Rahman, Hasimah & Majid, Md. Shah & Rezaee Jordehi, A. & Chin Kim, Gan & Hassan, Mohammad Yusri & O. Fadhl, Saeed, 2015. "Operation and control strategies of integrated distributed energy resources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1412-1420.
    3. Ted G. Eschenbach, 1992. "Spiderplots versus Tornado Diagrams for Sensitivity Analysis," Interfaces, INFORMS, vol. 22(6), pages 40-46, December.
    4. Cesar A. Vega Penagos & Jan L. Diaz & Omar F. Rodriguez-Martinez & Fabio Andrade & Adriana C. Luna, 2023. "Metrics and Strategies Used in Power Grid Resilience," Energies, MDPI, vol. 17(1), pages 1-16, December.
    5. Kharrazi, A. & Sreeram, V. & Mishra, Y., 2020. "Assessment techniques of the impact of grid-tied rooftop photovoltaic generation on the power quality of low voltage distribution network - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
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