Also worth noting in the same bundle of analysis is Friday 20th January 2023, which looked as follows (in terms of Aggregate Raw Off-Target across Semi-Scheduled units:
We see that, from around the time the sun rose on the day the vast majority of dispatch intervals feature collective under-performance. But this flips from around 15:25 with a bunch of instances of over-performance seen together, with the largest being AggROT = -497MW at 16:25 on the day.
This is another event that might be further explored in subsequent extensions to this Case Study.
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.
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.
It was inevitable that Semi-Scheduled plant would start to experience times when they are dispatched down. It’s a big prompt to take next steps up the learning curve.
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.
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