Given that it produced some pretty (significant and) strange outcomes in the NEM on the day (as noted in this initial article at the time) we’ll be reviewing this with keen interest… thanks to the WattClarity readers who alerted us about this!
… and, mainly for our own future reference as we find navigation on the AEMO website could be improved, this report is listed under ‘Scheduling Error Reports’ here.
Paul was one of the founders of Global-Roam in February 2000. He is currently the CEO of the company and the principal author of WattClarity. Writing for WattClarity has become a natural extension of his work in understanding the electricity market, enabling him to lead the team in developing better software for clients.
Before co-founding the company, Paul worked as a Mechanical Engineer for the Queensland Electricity Commission in the early 1990s. He also gained international experience in Japan, the United States, Canada, the UK, and Argentina as part of his ES Cornwall Memorial Scholarship.
As NEM wind power plants progressively work towards implementing FCAS, the criticality of ensuring that the power system either a) takes account of the variability in the wind forecasts coming from the wind power plants in the coming 5-7 minutes and follows the wind direction, or b) sets an appropriate dispatch level to ensure wind variability is minimized, becomes even more important for market and power system operators.
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.
Hot on the heels of Monday evening’s volatility, the AEMO has forecast LOR3 Low Reserve Condition (i.e. load shedding) might be possible in QLD on Tuesday evening.
Following up to AEMO’s recent Intermittent Generator forum, Marcelle looks at the challenges for wind and solar farms in providing consistently good plant availability information to AEMO and the value of transparency of this data.
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