Another short article today presenting an overview of Aggregate Raw Off-Target (AggROT) for Semi-Scheduled units on 16th February 2021 (the largest incidence of collective over-performance at that time).
Another short article today (from GenInsights Quarterly Update for Q3 2022) presenting an overview of Aggregate Raw Off-Target (AggROT) for Semi-Scheduled units on 23rd August 2022.
Another short article today (also from GenInsights Quarterly Update for Q1 2023) presenting an overview of Aggregate Raw Off-Target (AggROT) for Semi-Scheduled units on Friday 20th January 2023.
A short article today (whilst in the midst of finalising GenInsights Quarterly Update for Q1 2023) presenting an overview of Aggregate Raw Off-Target (AggROT) for Semi-Scheduled units on Friday 3rd February 2023.
In the fourth instalment of this ongoing case study, Dan Lee maps the locations and contributions of the semi-scheduled units that contributed to the +861MW Aggregate Raw Off-Target that occurred on the afternoon of October 27th 2022.
In Part 3 of this Case Study, we look at the source of the Dispatch Interval Availability forecasts for these units at 17:05 on 27th October 2022 (i.e. Self-Forecast or something else, incl AWEFS/ASEFS).
In Part 2 of this Case Study, we look at those 15 x Semi-Scheduled units highlighted with large deviations (mostly under-performance) at 17:05 on 27th October 2022 in order to understand more.
In today’s article (a third snippet from GenInsights Quarterly Update for Q4 2022) we take a look at levels of large ‘Aggregate Raw Off-Target’ (i.e. large collective deviations away from Target), which continue to grow for the Semi-Scheduled category and remind us of that question …
Allan O’Neil provides an explainer about how small deviations in supply and demand are managed in the NEM, in order to help us understand the apparent swings in frequency that we noted in QLD last Friday.
This 19th Case Study in the series investigates one dispatch interval showing extreme Aggregate Under-Performance across all Semi-Scheduled units on Friday 5th April 2019.
This 18th Case Study in the series investigates two separate dispatch intervals showing extreme collective under-performance across all Semi-Scheduled units on Monday 25th March 2019.
A quick look at this dispatch interval – as the 17th Case Study in the series looking at extreme results for Aggregate Raw Off-Target for all Semi-Scheduled DUIDs.
This 16th Case Study in a series covers the first ‘extreme event’ into 2019 where there was an aggregate under-performance (compared to Target) across all Semi-Scheduled plant totaling greater than 300MW.
Prompted, in part, by yesterday’s record low for Victorian demand, today I have finished off my earlier review of what happened on Saturday 29th August (8 days earlier) when demand levels also dropped in VIC, and right across the NEM.
This 15th Case Study is longer than the earlier 14 as it deals with 4 discrete instances of extreme level of collective under-performance, and 1 instance of over-performance, all within a 4-hour timeframe on the same day. A day which appears to have had widespread weather activity affecting the output of BOTH Wind and Solar across 3 Regions. A challenging day!
This is the 13th Case Study in this series (looking at each of 98 extreme incidents). We’re looking at an event on 15th October 2018 that seems to heavily feature high-wind cut-out as the primary driver for collective wind farm under-performance.
This is the 13th Case Study in this series (looking at each of 98 extreme incidents). Note I have skipped 2 events earlier in 2018 and will come back to publish case studies of them – this one covers the last event in 2018.
This is the 12th Case Study in this series (looking at each of 98 extreme incidents). This one is simpler than the 11th Case Study!
This is the 10th Case Study in a series working through 98 discrete dispatch intervals of extreme Aggregate Raw Off-Target for Semi-Scheduled events. This Case Study looks at only 1 of 5 occasions of extreme collective OVER-performance.
This 9th case study in this series advances us into October 2017, where we see another example of an extreme outcome for collective under-performance. Most notably this happens across 5 Wind Farms (with one unit completely tripping).