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Low-Voltage Network Modeling and Analysis with Rooftop PV Forecasts: A Realistic Perspective from Queensland, Australia

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  • Jake Anderson

    (Energy Queensland, Cairns 4870, Australia)

  • Ashish P. Agalgaonkar

    (School of Electrical, Computer and Telecommunications Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong 2500, Australia)

Abstract

Recent years have seen a rapid uptake in distributed energy resources (DER). Such technologies pose a number of challenges to network operators, which ultimately can limit the amount of rooftop solar photovoltaic (PV) systems that can be connected to a network. The objective of this industry-based research was to determine the potential network effects of forecast levels of customer-owned rooftop solar PV on Energy Queensland’s distribution network and formulate functions that can be used to determine such effects without the requirement for detailed network modeling and analysis. In this research, many of Energy Queensland’s distribution feeders were modeled using DIgSILENT PowerFactory and analyzed with forecast levels of solar PV and customer load. Python scripts were used to automate this process, and quasi-dynamic simulation (QDSL) models were used to represent the dynamic volt–watt and volt–var response of inverters, as mandated by the Australian Standard AS/NZS 4777. In analyzing the results, linear relationships were revealed between the number of PV systems on a feeder and various network characteristics. Regression was used to form trend equations that represent the linear relationships for each scenario analyzed. The trend equations provide a way of approximating network characteristics for other feeders under various levels of customer-owned rooftop solar PV without the need for detailed modeling.

Suggested Citation

  • Jake Anderson & Ashish P. Agalgaonkar, 2023. "Low-Voltage Network Modeling and Analysis with Rooftop PV Forecasts: A Realistic Perspective from Queensland, Australia," Energies, MDPI, vol. 16(15), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5834-:d:1211808
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    References listed on IDEAS

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    1. Vincent Umoh & Innocent Davidson & Abayomi Adebiyi & Unwana Ekpe, 2023. "Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review," Energies, MDPI, vol. 16(8), pages 1-25, April.
    2. Sam Wilkinson & Michele John & Gregory M. Morrison, 2021. "Rooftop PV and the Renewable Energy Transition; a Review of Driving Forces and Analytical Frameworks," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
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