It was now just over 5 years ago when Marcelle wrote ‘Not as simple as it appears – estimating curtailment of renewable generation’. This week's invocation of the 'N-DPWG_63_X5' constraint set provides a great...
A sequence of afternoon intervals stand out because the forecast appeared to be biased low – self-forecasts suddenly dropped roughly 30-40 percentage points and then increased a short time later.
Theoretically, if a self-forecasting system never offers forecasts for more than 60% of intervals it may perpetually skip the performance assessment and the system could continue for use unsuppressed.
Taking a guess at frequency need to earn a positive causer-pays factor through self-forecast biasing appears at-best uncertain in the intervals we review.
In another style of biasing a self-forecast, "lunar megawatts" represent an expectation of solar farm generation at night when it really should be zero.
The forecast differences would contribute to improved lower RMSE and MAE scores, relative to AWEFS_ASEFS, in the weekly performance assessment.
In today’s article (part 1 in this series) we present an example of biasing (at an unnamed solar farm), which we find aligns with FCAS cost mitigation.
We summarise how wind units are using self-forecasting to-date. The analysis leads us to consider where upcoming market change may lead the industry.
I've promised to write this article for some time, but a few recent events (and looming start of FPP) have caused me to publish this now.
Two weeks after the AER published its updated Compliance Bulletin (and Compliance Checklist) for Semi-Scheduled units, we've finally found time to note about it.
Semi-scheduled generators shouldn't treat self-forecasts as commercial parameters. The regulator holds significant concerns with the biasing of self-forecasts for commercial benefit.
A case study, drawing heavily on various widgets in ez2view, looking at some large (and unexpected) oscillations in output at Darlington Point Solar Farm through a ~2 hour period on Thursday 29th August 2024.
Gate Closure #3 represents the cut-off time for solar and wind availability forecasts to be used in dispatch. Since 2019 the timings are reducing and narrowing.
Our GSD2023 was released just over 4 weeks ago. This is the second sequential article utilising the GSD2023 Data Extract to take a look across all the Semi-Scheduled units (i.e. Wind and Solar). In...
This morning I was fortunate to listen into an ESIG Webinar with respect to their report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems'
It is indispensable to understand how the semi-scheduled unit availability gets produced to optimally manage the critical inputs and comprehend dispatch outcomes. This article explains the key inputs and processes, focusing on the dispatch...
AEMO is re-enabling the ‘MaxAvail’ figure in bids for Semi-Scheduled units. It will act as a limit on capacity available, feeding into the NEMDE dispatch process for the unit. We look at how Semi-Scheduled...
Today (Tue 23rd May) is the go-live date for AEMO's EMMS v5.2 - which will contain new data for some market enhancements. Here's a quick look at where this first change will appear in...
We delve deeper into dispatch availability self-forecasts and the assessment process to further enhance our understanding of this important aspect, testing sensitivity to gate closure times and requirements on minimum intervals.
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).