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6.5.3 Upscaled curtailed generation & emissions impact
• Medium loss case: it is assumed that half of the curtailed energy was during net-export conditions (energy that could be exported if it were not curtailed) and other half during netimport conditions (the energy that could be self-consumed if it were not curtailed). Therefore, half of the loss revenue is calculated at 10c/kWh and the remaining half is calculated from an average import tariff of 30 c/kWh. • High loss case: it is assumed that all curtailed energy was during net-import (energy that could be self-consumed if it were not curtailed) and therefore, loss revenue is calculated from an average import tariff of 30c/kWh. The average FiT and import tariff rates were selected according to rates available for South Australian energy users [47] and the distribution of loss revenue due to curtailment is shown in Figure 46 below.
Figure 45 Financial revenue loss for D-PV owner energy users due to tripping (anti-islanding and limits for sustained operation) and V-VAr curtailment for three cases (low loss case, medium loss case, and high loss case) and three scenarios (real, TS-129 and ENA)
Revenue loss due to tripping and V-VAr curtailment is not significant for majority of the D-PV system owners as per the analysed Solar Analytics fleet. On average, the loss is less than $5/year regardless of the analysed scenario. On the other hand, similar to the BESS results, a small number of households lose more significant revenue as seen with the outliers which can be as high as $100/year. The results show that, on average, the lost revenue due to curtailment is higher for the D-PV only sites compared to BESS sites, aligned with the results presented in Table XIII. Another important point to emphasize is that most D-PV sites would lose less revenue due to curtailment if their D-PV inverters show the required V-VAr response rather than showing VAr response as a function of real power.
This section provides an estimate for the upscaled curtailed generation and its emissions impact. It is critical to emphasize that these estimates include major assumptions that limit the extent to which the findings can be generalised, one of which is the fact that the analysed sites may not be representative of the DER fleet across Australia. In particular, Solar Analytics energy users tend to have higher awareness and knowledge around DER and energy related topics than the general DER owner. It can also be assumed that households that participate in a VPP trial are likely to be more engaged in DER and energy related topics than the general DER owner. Furthermore, the majority of the Solar Analytics and AGL VPP energy users have more recent D-PV/BESS installation dates compared to general DER owner which will result
