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

Jake Anderson and Ashish P. Agalgaonkar ()
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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

Energies, 2023, vol. 16, issue 15, 1-23

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.

Keywords: distributed energy resource; solar PV penetration; voltage rise; network constraints; network modeling automation; reverse power flow; inverter energy systems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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