This document presents a smart meter-driven analytical technique proposed by The University of Melbourne to estimate PV hosting capacity in distribution networks.
Report extract
This report corresponds to “Deliverable 2: Innovative Analytical Techniques” part of the project Advanced Planning of PV-Rich Distribution Networks with funding assistance by the Australian Renewable Energy Agency (ARENA) as part of ARENA’s Advancing Renewables Program and led by the University of Melbourne in collaboration with AusNet Services. The project is established to develop analytical techniques to assess residential solar PV hosting capacity of electricity distribution networks by leveraging existing network and customer data. Additionally, planning recommendations will be produced to increase the hosting capacity using non-traditional solutions that exploit the capabilities of PV inverters, voltage regulation devices, and battery energy storage systems.
This document focuses on the methodology and assessment of a smart meter-driven analytical technique proposed by The University of Melbourne to estimate PV hosting capacity in distribution networks; two significantly different HV feeders, urban and rural, are considered. This document starts with some additional modelling aspects relevant to the modelling of HV-LV feeders. Then, the smart meter data provided (by AusNet Services) for the purposes of this project are detailed. Given the importance of using large volumes of smart meter data to explore and understand the relations between customer data and network state under different PV penetration levels, a methodology to produce realistic (hybrid) smart meter data for a horizon of 5 years is proposed.
Lastly, this report presents the proposed analytical technique that makes use of smart meter data to construct a statistical regression model for each LV network, in a given HV feeder, and estimate its corresponding PV hosting capacity. The performance of the proposed hosting capacity estimation (HC estimation) methodology is assessed under three different PV system uptake trends, as well as considering the effects of network controllable elements such as the zone substation OLTC.