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- W2490003670 abstract "In power systems rife with uncertainty, stochastic unit commitment (SUC) models may be used to properly size and allocate operational reserves, in order to ensure a reliable and cost-efficient operation of the power system. The performance of SUC-based unit commitment schedules is however fully dependent on the scenario sets used to describe the uncertainty at hand. Dedicated scenario generation & reduction techniques (SGT & SRT) have been developed to generate and select scenario sets that capture the uncertain parameter, e.g. wind power, and yield a cost-optimal unit commitment (UC) schedule in reasonable computing times. Probability-distance based SRTs are by far the most used. In an extensive numerical study, we analyze the performance of so-called cost functions used in these SRTs. In addition, we propose a new cost function, which allows selecting a well-balanced subset of scenarios, resulting in a tractable SUC model and a cost-optimal UC schedule." @default.
- W2490003670 created "2016-08-23" @default.
- W2490003670 creator A5023410209 @default.
- W2490003670 creator A5090101671 @default.
- W2490003670 date "2016-04-01" @default.
- W2490003670 modified "2023-10-18" @default.
- W2490003670 title "Scenario reduction techniques and solution stability for stochastic unit commitment problems" @default.
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- W2490003670 doi "https://doi.org/10.1109/energycon.2016.7514074" @default.
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