Every day at wind plants across the United States, there's an important daily task that's approached as a matter of routine. That task is providing the required schedule of tomorrow's expected wind output for the day-ahead electricity market. Typically, the professionals carrying out this task are risk adverse, and often use simple rules of thumb to submit their day-ahead schedules. One such example is submitting only half of the expected output to minimize the risk of getting caught short in the real-time market, with the view that everything will "settle out" in the real-time market. However, experience suggests this is a major lost opportunity - potentially, by as much as three gigawatt-hours (GWh) for an average-sized, 100-megawatt (MW) plant every month. Although wind plant energy schedulers would likely agree there's more money to be made with a risk-adjusted scheduling strategy for the day-ahead market, they often lack the tools and information required to extract additional value from this daily routine. The solution: a better understanding and exploitation of probabilistic forecasts, which would allow more energy to be scheduled into the day-ahead market, without increasing the risk of under-delivering any power.
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