6.3.4 Volt-var curtailment (scenarios

Figure 39 Monthly distribution of generation curtailed by V-VAr characteristic for the 100 Solar Analytics sites with highest VArs

In previous sections, it was seen that the majority of BESS and D-PV inverters do not show any V-VAr response. Therefore, the obtained V-VAr curtailment results are not representative of the ideal case where each BESS and D-PV inverter would show the required V-VAr response according to local voltage conditions and relevant standards.

The V-VAr scenario analysis conducted tries to address this point and aims to present results that are more representative of DER future where majority of BESS and D-PV inverters are installed with the respective V-VAr response mode by default. The scenario analysis results are firstly presented for BESS systems from AGL dataset followed by D-PV systems Solar Analytics dataset. 6.3.4.1 AGL dataset Similar to the V-VAr curtailment analysis applied on real operational data from BESS, V-VAr scenario analysis is carried from both energy user’s and aggregator’s perspective. Figure 41 shows the distribution of percentage of total generation curtailed by V-VAr according to the studied V-VAr curves (see Figure 9) from the energy user’s perspective. The results are presented alongside the real measured data. The following Table X presents the key summary statistics for each distribution. It is seen that V-VAr curtailment from the energy user perspective is higher under the modelled V-VAr scenarios compared to the actual case. However, V-VAr curtailment is still insignificant, less than 1% of total generation under all analysed scenarios. Amongst the four analysed V-VAr curves, the ENA recommendation results in the highest amount of V-VAr curtailment and AS 4777-2015 results in the smallest amount of V-VAr curtailment.

Figure 40 V-VAr curtailment scenario analysis for all AGL VPP sites (energy user’s perspective)

Table X Summary statistics for V-VAr curtailment scenario analysis for all AGL VPP sites (energy user’s perspective): percentage of total generation curtailed (%)

Real TS-129 AS4777_2015 ENA AS4777_2020

min 0 0 0 0 0 max 0.06 0.17 0.16 0.27 0.17 mean 0.01 0.01 0.01 0.02 0.01 median 0 0.01 0.01 0.01 0.01

Figure 42 shows the distribution of percentage of total generation curtailed by V-VAr according to the studied V-VAr curves (see Figure 9) from the aggregator’s perspective. The results are presented alongside with the real case. The following Table XI presents the key summary statistics for each distribution. Once again, the modelled V-VAr response results in higher V-VAr curtailment than the real case. The increase in V-VAr curtailment is higher for the aggregator’s perspective (includes curtailment instances when both charging and discharging) than the energy user’s perspective (only focuses on curtailment during instances of discharging and net-import). Amongst the studied V-VAr curve scenarios, the ENA recommendation results in significantly higher V-VAr curtailment. This is especially due to ENA’s more aggressive VAr absorption recommendation at 60% VAr/VA_rated. The V-VAr curtailment results are very similar between TS-129 and AS/NZS 4777-2020 and smallest for AS/NZS 4777-2015.

Figure 41 V-VAr curtailment scenario analysis for all AGL VPP sites (aggregator’s perspective)

Table XI Summary statistics for V-VAr curtailment scenario analysis for all AGL VPP sites (aggregator’s perspective): percentage of total generation curtailed (%)

Real TS-129 AS/NZS 4777-2015

ENA AS/NZS 47772020

min 0 0 0 0 0 max 0.06 0.27 0.17 0.85 0.28 mean 0.01 0.03 0.02 0.10 0.04 median 0 0.02 0.01 0.08 0.02

6.3.4.2 Solar Analytics dataset Figure 43 shows the distribution of percentage of total generation curtailed by V-VAr according to the studied V-VAr curves (see Figure 9) from D-PV inverters. The modelled scenario results are presented alongside the data from the real case. The following Table XII presents the key summary statistics for each distribution. It is seen that average V-VAr curtailment is insignificant both for the real case and the studied scenario analysis. However, for some D-PV inverters with different VAr and PF behaviour (see Section 6.3.2) experienced curtailment was greater in real case compared to operation according to one of the reference V-VAr curves. It is also seen that when these D-PV inverters operate according to one of the V-VAr curves, the extreme V-VAr curtailment cases diminish as seen by the narrower distribution range compared to the real case. Amongst the studied V-VAr curves, the ENA recommendation causes the highest average V-VAr curtailment followed by AS/NZS 4777-2020, TS-129 and AS/NZS 4777-2015.