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As wind power output cannot be adjusted like conventional power output of generators, wind power should track the generating schedule using wind power forecasting when it is considered in the dispatch framework.
The former three decide the generating schedule and then the generating schedule is sent to relative control unit and the latter executes the instruction.
A strategy is proposed for making generating schedule, by combining day-ahead unit commitment with empirical probability density function of forecasting errors [11, 12].
To the contrary, the generating schedule made by the proposed method will lead to less power shortage. .
To the contrary, the generating schedule made by the proposed method will lead to less power shortage.
When wind power is integrated into the power system, correspondingly, short-term wind power forecasting can be utilized to make day-ahead and daily generating schedules, while ultra-short-term wind power forecasting can be utilized to make on-line generating schedule and allocation of active power in WFs.
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Prior generating schedules, we also discuss how to reduce the number of state inconsistency and detect them if occurred.
So the generating schedules of the WF cluster made by both methods can well track the dispatch command when forecasting confidence is high enough.
Scheduling for flexible manufacturing systems (FMS) poses the challenge of optimizing the generated schedule while exhibiting flexibility to environmental dynamics.
The best generated schedule of instructions with a MaxLive = 12 was computed within 2- to 15-min range.
Nguyen et al. [88] proposed iterative dispatching rules (IDR) which are able to create multiple schedules iteratively and the new schedule is generated based on the information of the previous generated schedule (e.g. completion times of jobs).
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