2.6 Key gaps that CANVAS aims to address

study by Howlader et. al. studied different D-PV grid support functions such as Frequency-watt, V-Watt and a fixed curtailment setting on a feeder serving a residential neighbourhood on the island of Maui, Hawaii [39]. The authors found that frequency-watt and V-Watt modes were effective in controlling the frequency and voltage of the local LV network, respectively. Perhaps one of the earliest studies regarding D-PV curtailment was carried out in Japan. Ueda et. al. collected and used high-resolution D-PV generation data from 533 households alongside with irradiance and temperature to estimate D-PV curtailment [40]. The study found that only a few households experienced significant D-PV curtailment due to high grid voltages and on average curtailment was small. Authors attributed the uneven distribution of curtailment to the differences of line impedance, D-PV inverter settings as well as the imbalance of the loads along the distribution network. Procopiou et. al. investigated V-VAr’s capability in managing local high voltages in a UK case study [41]. In contrast to previous studies, the authors concluded that V-VAr’s capability of regulating voltage was rather limited because D-PV inverters prioritised real power output which limited their capability to absorb VArs during high voltage events. Based on the analysed real-operational data our study, we found conflicting evidence with [41] such that some D-PV inverters were capable of absorbing VArs in higher quantities than real power output during high voltage instances. Furthermore, the studied BESS in our study showed that they are capable of absorbing VAr at their rated VA capacity. Shaughnessy et. al. compared utility scale PV curtailment across Germany, China, Chile and four states of USA [22]. The study found that the analysed utility scale curtailment events were mainly driven by the mismatch of supply and demand. Authors emphasised that in this context a shift is required in the perception of curtailment, as it may also help in achieving optimal grid management rather than being solely associated with ‘loss’. However, curtailment of consumer DER raises a range of different issues around equity of distribution of impacts, transparency, and knowledge of curtailment risk both prior to and after investment in DER.

The literature review presented here has shown that there have been a limited number of studies that have analysed D-PV curtailment using real operational data. Furthermore, even though some studies had real operational data, the data was either limited by the number of sites or duration of the dataset. Moreover, there seems to be a missing link between analysis of the social and technical aspects of DER curtailment as most studies tend to focus more on the technical side of DER curtailment without considering its social dimensions. And finally, most of the existing studies have focused on D-PV curtailment, as the availability of real operational data from BESS has been very limited to date. Considering these points, the unique contributions of CANVAS can be listed as follows: • Tripping (anti-islanding and limits for sustained operation) and V-VAr curtailment analysis carried out on high-resolution data from 996 BESS (12-months) and 500 D-PV (10-months) sites in metropolitan Adelaide. • V-VAr curtailment analysis based on real operational data in Australia (to the authors’ knowledge, this is the first Australian study analysing V-VAr curtailment using real operational data). • Comparison of curtailment between D-PV sites against BESS sites (to the authors’ knowledge, this is the first Australian study comparing curtailment between D-PV and BESS using real operational data). • Integration of social science and technical data analysis components to provide key sociotechnical insights regarding DER curtailment in Australia (to the authors’ knowledge, this is the first Australian study to bring together social and technical insights on DER curtailment).